Detecting online commercial intention (OCI) Understanding goals and preferences behind a user's online activities can greatly help information providers, such as search engine and E-Commerce web sites, to personalize contents and thus improve user satisfaction. Understanding a user's intention could also provide other business advantages to information providers. For example, information providers can decide whether to display commercial content based on user's intent to purchase. Previous work on Web search defines three major types of user search goals for search queries: navigational, informational and transactional or resource [1] [7] . In this paper, we focus our attention on capturing commercial intention from search queries and Web pages, i.e., when a user submits the query or browse a Web page, whether he / she is about to commit or in the middle of a commercial activity, such as purchase, auction, selling, paid service, etc. We call the commercial intentions behind a user's online activities as OCI (Online Commercial Intention). We also propose the notion of "Commercial Activity Phase" (CAP), which identifies in which phase a user is in his/her commercial activities: Research or Commit. We present the framework of building machine learning models to learn OCI based on any Web page content. Based on that framework, we build models to detect OCI from search queries and Web pages. We train machine learning models from two types of data sources for a given search query: content of algorithmic search result page(s) and contents of top sites returned by a search engine. Our experiments show that the model based on the first data source achieved better performance. We also discover that frequent queries are more likely to have commercial intention. Finally we propose our future work in learning richer commercial intention behind users' online activities. There are two major online user activities on the Web. The first type of user activities is the well-studied browsing activity, i.e., how user visits Web pages on one or more Web sites. The second type, searching activity, is under great attention recently. Since the past decade, people started to study the phenomenon of search engines, their impact and user search behavior by surveying, statistical log analysis, and search presentation study [1] [3] [6] [7] [8] . A comprehensive review on Web searching studies can be found in [13] . Recently there has been more and more work being done in the field of understanding goals and intention of search users. Understanding goals and preferences behind user's search activities can help different types of information providers (e.g., search engines, E-Commerce sites, and online advertising businesses), to personalize search results and thus improve user satisfaction. Pilot research and applications can be found in [11] [10] [2] [12] and [14] .. In [1] and [7] , user's search intention / goals were classified into three general categories: Navigational, Informational and Transactional or Resource. The goal of a navigational query is to reach a particular web site; the intent of an informational query is to acquire information on web pages; and a user who inputs transactional queries are to perform some "web-mediated" activity. User search goals can also be represented using topical categories ( [18] [9] and [22] ) or location attributes [21] . A few efforts have been invested in automatically identify user search goals [4] [10] [20] [21] .. Often times, information providers would like to know whether a user has intention to purchase or participate in commercial services, which we call "Online Commercial Intention" or OCI. Online Commercial Intention has broader scope than general search intention discussed in [1] and [7] . First of all, OCI can be applied on both searching and browsing activities. Secondly, OCI of a search user can be seen as another independent dimension of search intention besides the three categories: Navigational, Informational and Transactional / Resource. Table 1 shows that Online Commercial Intention (OCI) can cover all three of the previously defined types of search goals and can be seen as a new dimension of user search goals. In addition, Online Commercial Intention can be further extended to reflect what phase a user is in during a user's commercial activity. We call it Commercial Activity Phase (CAP). Usually online users will do some research before making their mind to purchase. Therefore we define two Commercial Activity Phases: Research and Commit. During research phase, users may search for general information of their need, look at product information and reviews, search for deals, compare prices, etc. They may come to commit phase when they make up their mind. Usually at this phase users will reach the transaction pages, or go offline to complete the commercial activity.. Knowing Online Commercial Intention (OCI), information providers could adopt different strategies when providing service to users who intend to purchase versus the users who don't intend to purchase. For example, commercial intention can be integrated into any recommender system's ranking algorithm so that recommendation results can be ranked based on the OCI. Another advantage of learning commercial intention is that information providers can detect user's commercial value. A user submits query "who is the 20th president of United States" has little commercial value, while the user who submits query "honeymoon suite in Maui" is much more attractive to Ecommerce Web sites, search engines or advertisers because they are more likely to be online shoppers.. When studying Online Commercial Intention (OCI), we can learn individual users' intention from their behavior; we can also understand the general intention at the level of search queries or Web pages. In this paper, we focus our attention on OCI of search queries or Web pages.. We define online commercial Intention (OCI) to be a function from a query or Web page to binary value: Commercial or NonCommercial. More specifically, if the general purpose of users submitting a query or visiting a Web page is to commit a commercial activity, such as purchase, auction, selling, or paid service, the query / Web page will be treated as Commercial. If accessing the query or the Web page has little to do with any commercial service or activity, the query / Web page is considered as non-commercial.. There are several challenges in determining OCI from search queries. First of all, most search query terms do not explicitly contain terms that tell commercial intention. We found that only a small percentage of search queries have explicit terms indicating commercial intention. Furthermore, search queries are usually very short. According to [13] and [6] , the average length of search queries in general purpose search engines is about two terms. Therefore, we will need help from external data sources in order to capture queries' online commercial intention.. In the last two years, there have been studies in learning different types of attributes from search queries by means of external information. In [10] , authors adopted multiple types of information, e.g., different query term distribution in independent document set, mutual information, the usage rate as anchor texts, and POS information, to classify search query into navigational or informational categories. The same query categorization problem was visited again by Lee et al. [20] . They built query classifiers based on past user-click behavior and anchor-link distribution to achieve the same query categorization problem. Lee Wang et al. [21] built location information detector based on multiple data sources, including query result page content (snippets) and query logs. In [15] , similarity between two queries was computed from both the keywords similarity and the common search result landing pages selected by users. For Web pages, the problem is less serious because pages are usually longer than search queries.. Subjectivity of the definition of OCI is another challenge for both search queries and Web pages. Some search queries / Web pages may be ambiguous in their senses of commercial intention. A user may be interested in learning the non-commercial side of the information about a commercial product/service. However, because we consider the general purpose of the query/Web page, i.e., the purpose that is agreed by majority of users who used this query, we assume that an average online user has a commercial intention if he/she accesses a query or a Web page about a commercial product or service. We will discuss the details of labeling process in 4.2.. In this paper, we present a solution to detect online commercial intention (OCI). The contributions of this paper include: 5. An interesting finding about the relation between query frequency and query's OCI.. The rest of this paper is arranged as following: Section 2 introduces the definition of OCI and section 3 discusses our methodology of building machine learning models to detect OCI from search queries and Web pages. Section 4 presents experiment and evaluation. In section 5 we propose future work in learning the online commercial intention framework and related applications. The goal of this paper is to detect commercial intention from search queries and Web pages, i.e., when a user submits a query or browses a Web page, whether he / she is about to commit or is in the middle of a commercial activity, such as purchase, auction, selling, paid service, etc. We call the commercial intentions behind user's online activities OCI (Online Commercial Intention).. We also proposed the notion of "Commercial Activity Phase" (CAP), which identifies in which phase a user is in his/her commercial activities: Research or Commit.. We present the framework of building machine learning models to learn OCI based on any Web page content. Based on that framework, we build models to detect OCI from search queries and Web pages. Our framework trains learning models from two types of data sources for a given search query: content of returned first search result page and content of top pages returned by search engine. Our experiment showed that the model based on the first data source, i.e., returned first search result page content, achieved better performance.. We also discovered an interesting phenomenon that frequent queries are more likely to have commercial intention.. We will continue improving our algorithm to address the following issues:. 1. Labeling effort. We are working on reducing labeling cost and subjectivity to improve the performance of the commercial intention detector. How to reduce the human subjectivity and automate labeling process is our next immediate task. We are interested in semisupervised learning techniques to exploit the massive amount of unlabeled data.. 2. Finding more effective and efficient features. In the future we will consider using other sources of data such as click data if it is available for the query.. 3. Improving performance. Current solution requires sending queries to search engine, which make the unit response time rely on the search engine's response time.. Solutions based on search result landing pages costs more time due to the cost from crawling top N pages. We will look into a more efficient method to obtain the context of search queries. We will also work on a better solution to find explicit commercial indicators, such as phrase-based solution.. 4. Detecting Commercial Activity Phase (CAP). Current solution can detect whether or not a user has intention to commit a commercial activity. However, if we could tell at what stage the user is in the commercial activity, and how far it is to reach the actual purchase or other commitment, we could provide better personalized information service to individual users.. 5. Detecting individual user's OCI based on his/her online behavior throughout an online session. Our current effort is focused on detecting general OCI for search queries or Web pages. However, as we have mentioned earlier, different users may have different intentions when accessing the same search query or Web pages, or may have different intentions on the same query in different phase of a purchase process. It will be interesting to consider the user session or online history as a whole unit to evaluate the user's OCI. It will be also worthwhile to investigate the evolution of a user's OCI over time.

O B I I B O B O O O O O B O O O B O O O O B O O O O O O O O O O O B O O O O B O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O B O O O B O B B B O B B O O O O O B O O O O O B O O O B O O O B O B B O O O O O O B O O B O B O B I O O O O O O O B O O O O O O O O O O O B O O O O O O O O O O O O B O O B B I I O O O O O O O O O O O O O O O O B O O O O O B O B O O O B O O B I O O O B O O O B I O O O O B O O O O O B O B B O O O O O B I O O O B O B O O O O B B O O O B O O O O O O O O O O B O O O O O O B O O O O B O O O B O O O O O B O O O O O O B O O O O B O O B O O B O B B O O O O O B B O O O O O O O O B O O O O O O O O B O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O B O O O O B B O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O B O B B O B O O O O B O O B O B O O O O B O O O O B O O O O B O O O O B O O B O O O O O O O O O O O O O O O O O O O B I O B O O O O O O O O O O O B O O O O O B O O O O O B I O O O O O B O O O O O O O O O B O O O B O O O O O O B B B O O O O O O O O O O O O O O O O O O O O O O O O O O O B B B O O O O O O O O O O O O O O O B O B O O O O O O O O O O B I I O B B I I O O O O O B I O O O O O O O O O B O O O O O O O O O O B O O B B O O O O O O O O B I O O O O O O O O O B O O O O B I I B O O O O O O O O B O B B O O O O O O O O O B B B O O B I I O O O O O O O O O B O O O O O O O O O O O O O O O B B O O O B O O O O O O O O O O O O O B O B O B O B O B O O O O O O O O O O O O B O O O O O O O O O B O O O O O O O O O O O B O O O B O O O O O O O O O O B I I B O O O O O O O O O O B O O O O O O B O O O O O O O O B O O O O O O O O O O O O O O O O O O O B O O O B O B O O O O O O O O O O B O B O O O O O O O O O O O O O O B O O B O O O O O O O O O O O O B O O O O O O O O O O B O O O B I I B O O O O B B O O O O O O O O O B O O O O B B O O O O O B O O O B O B O B B O O O O O B I I B O O O O O O B O B I O O O O O O O O O O O O O B O O B O O O B I O O B O O O O O O B O O O O O B O B I O O O O O O O O B O O B I O O O O O O O O O O O B O B I O O O O O O O O O O B O B B O O O O B B O O O O O O O O O B O O O O O O O O B B O O O O O B O B B O O O O O O O O O O O O O O B B O O O B O O O O O O O O O B O O B O O O O O B B I I O O O O O O O O O O B O B O O O B B O O O O O O O O O O O B O O O O B O O O O O O O O O O O O O O O O O O O B B O O O O O O O B O O O O O O O O O O O O O B O O O O O O O O O O O O O B O O O O O O O O O O O O O O B O O B O O O O O B O O O O O O O B O O O O O O O O O O B O O O O O B O O O O O O O O O O O O O O B B O O O O O B O O O O O B B O O O O B B O O O O O O O O O O O B O B O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O B O O O O O B B O O O B O O O O B O O B I O O O O O O O O O O O O O O O O O O B O O O O O O B I I B O O O O B O O O O O O O O O B O O O B O O O O B O O O O O O O O O O B O O O O O O O O B I O O O B O B B O O O O O O O O O O O O O O B O O B O B I I B O O O O O O O B O O O O B O B B O O O O O O B O O B O O O B I O O O O O O O B O O O O O O O O O O O O B O O O O O O O O O O O B O B B I I O O O O O O O O O O O O O O O O B O O O O O B O B O O O B O O B I O O O B O O O B I O O O O B O O O O O B O B B O O O O B O B O O O B O B O O O O B B O O O O B O O O O O O O O O B O O O O O O B O O O O B O O O O B O O O O O B O O O O O O O O B O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O B O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O B O O O O O O O O O B O O O O O O O B O O O B O O O O O O B O O B O O O O B O B O O O O O O O O O O B O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O B O B O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O B O O O B O O O B O O O O O O O O O B O B B O O O O O O O O O O B O O O O O O O O B B O O O O O O O O O O O B O O O O O O O O O O O O O O B O O B O O O O O O O O O B O O O O O O O O O O O O B O O


An innovative method for data and software integration in SaaS Recently the main trend in providing software services has been shifting from an ASP (application service provider)-oriented to a SaaS (software as a service). ASP is a software service model in which the service is provided on a one by one basis according its ownership, while SaaS is a software service model in which the service is provided virtually on a one by one basis, but physically all at once. In a SaaS environment, all users can access the system via Internet without any software installation-examples include Google and Amazon. Now, more companies are shifting their business software service from ASP to SaaS. However effecting the transition of the existing software and data from ASP to SaaS is not an easy task. First, we have to solve the problem of the integration of data for different forms of software, because each data set consists of different data types. Second, the software integration must support a user customizing interface for various users on the Web. Almost all users want customized services, but those require high costs. In this paper we propose a novel method for transferring the existing business software to integrated software that can be used in the SaaS environment. We use a master table and master code to implement the integrated system. The master table is based on the project master table, and other user information tables are connected to collect the necessary information. All information about the project is stored in each column of the project master table. The master table can integrate various software databases. By using this novel methodology, the existing ASP-based software and data can be effectively transferred to the SaaS environment. Modern society is an information-oriented society, wherein smart ideas and talent are important, beyond the resourceand labor-oriented industrial society. In the past, businesses made profits only from product sales, and advertised for maximized profits or tried to reduce costs within the scope of traditional ways. However, this type of profit-seeking business had limitations, and businesses started to find a new way to achieve their desired results at a low cost. Businesses tried to change their business processes, adopted the ideas of their employees, and collected ideas even from outside.. The results of such efforts first appeared in the advertising industry. In the earlier period of the industry, celebrities appeared in advertisements and promoted products. Diverse kinds of advertisements appeared with unique and exciting ideas, and people were interested in them [1] .. The low-cost and high-efficiency principle was also applied to in-house business processes. Instead of a traditional system of document approval, the ideas of employees were collected and managed, and an electronic approval system was introduced to change the in-house business culture [2] .. Using enormous capital, large enterprises introduced the business management system that suited for them. The system was exclusively developed for each enterprise, to manage its tasks, results, and service evaluations. Therefore, it could not be applied to other enterprises. Because of its very high cost, small and medium-sized enterprises could not afford to construct their own systems. To address this problem, the software as a service (SaaS) type of business support system was developed. The SaaS method allows the user to use the software provided by the developer via the Internet for a monthly charge. This method eliminates the need for users to establish a system by themselves or purchase the specific software. The SaaS system does not require a higher cost for an initial installation, and can be directly customized by the user. Therefore, the user can select his/her desired software and use it. Because this system was developed in compliance with Web standards, it also can be used by different users. This is a very efficient software distribution method [3] .. In this study, we propose a novel method for integrating existing softwares in the SaaS environment. This method can be applied to all the commercial softwares, and we illustrate business software integration using the proposed method. The integrated software is service-oriented through Internet access, where the customers only pay for the service that they want to use. This paper is organized as follows. We first discuss cloud computing, ASP and SaaS, with several service-oriented methods such as IaaS and PasS being treated in detail, in Section 2. After that, we propose a master table method for organizing the SaaS service. Section 4 explains the simulation results and is followed by a conclusion in Section 5. In this paper we propose a novel method for integrating existing software into a SaaS environment. We use a master table and master code to solve the associated problems. The master table is based on the project master table, and other user information tables are connected in order to organize user information. All information about the project is stored in each row of the project's master table. The master table can integrate various software databases. By using this novel method, the existing ASP-based software and data can be effectively transferred to the SaaS environment.. It is expected that SaaS will provide a new software distribution stage because users can select and use the required functions on paying only a small monthly fee instead of purchasing the software at a high cost. The master table methodology could be a core technology in solving database problems that may occur in software integration.

O O O O O O B I O B O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I


Informing the design of the future urban landscape This workshop will identify emerging themes that will impact on the design of the urban environment, through exploration of the boundaries between the virtual and physical worlds. Participants in the workshop will collaborate in a practical exercise designed to act as a stimulus for thought concerning the nature of the products and services that will populate the urban landscape in the near future. The outcome of the workshop will be the identification and description of a series of issues that designers and technologists will have to address as they shape the interactions within the media-rich urban landscape. This will form the basis of new collaborative networks with the aim of taking this technological design research agenda further. It is envisaged that the urban spaces of the future will be saturated with both visible and hidden media that gather and transmit information. How we as physical beings connect with, interpret and shape the increase of data residing in our environment will be a significant challenge. The forms in which this data will be presented, and how we decide to conceptualise it, are as yet unknown. Will the technologically enriched environment adapt to accommodate human/city contact points, and, in response, how will we choose to interact with and navigate through, this information landscape? Today's urban experience is Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. enhanced by technology that increasingly enables simultaneous existence in both the virtual and real worlds.. There is an increasing trend towards the use of aggregate data when projects seek to reveal or make explicit invisible urban phenomena such as pollution, noise, patterns of movement and peoples' emotional reaction to places. The city has become a kind of 'blogject' that provides data for applications and services that seek to visualize urban dynamics in real time thereby helping individuals to make informed decisions about how they behave in the physical environment. Examples of such prototype systems include Christian Nold's Biomapping [1] , mapping emotional arousal with geographic location; Tripwire [2] by Tad Hirsh monitored noise pollution while Sensing Atmosphere [3] measured air pollution. Each of these prototypes provide different ways for viewing, interpreting and interacting with the urban environment Such technology offers a number of bridges between these worlds but in so doing places an increased tension on the sense of place and subsequently the identity of the individual. Identity has many components that have to be woven in our everyday lives. It is postulated that in order to cope with the demands of our society, people must be capable of switching between identities actively and quickly while stitching these different identities in place [4] . Furthermore, it is possible that a 'fragmentation' of identity is part of our experience of modernity [5] . Today identity is just as much about stitching multiple identities in separate virtual places as it is with their physical counterparts. Our sense of place, both physical and virtual, contributes to our feeling of presence and the subsequent identity that is created, maintained and communicated. It is at the border of these physical and virtual worlds that the urban dweller's sense of place resides and it is through collaborative enquiry, using techniques such as those to be employed in this workshop, that the crossing points can be identified and shaped.

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Monadic datalog and the expressive power of languages for Web information extraction Abstract. Research on information extraction from Web pages (wrapping) has seen much activity recently (particularly systems implementations), but little work has been done on formally studying the expressiveness of the formalisms proposed or on the theoretical foundations of wrapping. In this paper, we first study monadic datalog over trees as a wrapping language. We show that this simple language is equivalent to monadic second order logic (MSO) in its ability to specify wrappers. We believe that MSO has the right expressiveness required for Web information extraction and propose MSO as a yardstick for evaluating and comparing wrappers. Along the way, several other results on the complexity of query evaluation and query containment for monadic datalog over trees are established, and a simple normal form for this language is presented. Using the above results, we subsequently study the kernel fragment Elog − of the Elog wrapping language used in the Lixto system (a visual wrapper generator). Curiously, Elog − exactly captures MSO, yet is easier to use. Indeed, programs in this language can be entirely visually specified. The Web wrapping problem, that is, the problem of extracting structured information from HTML documents, is one of high practical importance and has spurred a great amount of work, including theoretical research (e.g., Atzeni and Mecca [1997] ) as well as systems. Previous work can be classified into two categories, depending on whether the HTML input is regarded as a sequential character string (e.g., TSIMMIS [Papakonstantinou et al. 1995] , Editor [Atzeni and Mecca 1997] , FLORID [Ludäscher et al. 1998 ], and DEByE [Laender et al. 2002] ) or a preparsed document tree (e.g., W4F [Sahuguet and Azavant 2001] , XWrap [Liu et al. 2000] , and Lixto [Baumgartner et al. 2001b [Baumgartner et al. , 2001a Lixto] ). The latter category of work thus assumes that systems may make use of an existing HTML parser as a front end.. From the standpoint of theory, many practical problems are presumably simpler to solve over the parse trees of documents rather than over the documents considered as strings. 1 In the light of the large legacy of Web documents that motivate Web information extraction in the first place, the practical perspective of tree-based wrapping must be emphasized. Robust wrappers are easier to program using a wrapper programming language that models documents as preparsed document trees rather than as text strings. Writing a fully standards-compliant HTML parser is a substantial task, which should not have to be redone from scratch for each wrapper being created. The use of an existing parser allows the wrapper implementor to focus on the essentials of each wrapping task and to work on a higher, more user-friendly level. No serious study of the productivity gains obtained by the transition from string-based to tree-based wrapping has been conducted as of yet, but we think that it is clear that the leap in productivity must be substantial.. Nonlinear productivity improvements in software development are among the most desirable and valuable outcomes of computer science research. The oftenobserved information overload that users of the Web experience witnesses the lack of intelligent and encompassing Web services that provide high-quality collected and value-added information. At the origin of this, there is a mild form of software crisis in Web information extraction which calls for such productivity improvements.. A second candidate for a substantial productivity leap, which in practice requires the first (tree-based representation of the source documents) as a prerequisite, is the visual specification of wrappers. By visual wrapper specification, we ideally mean the process of interactively defining a wrapper from one (or few) example document(s) using mainly "mouse clicks", supported by a strong and intuitive design metaphor. During this visual process, the wrapper program should be automatically generated and should not actually require the human designer to use or even know the wrapper programming language. Visual wrapping is now a reality supported by several implemented systems [Liu et al. 2000; Sahuguet and Azavant 2001; Baumgartner et al. 2001a] , however with varying thoroughness.. Little is known about the theoretical aspects of tree-based wrapping languages. Clearly, languages which do not have the right expressive power and computational properties cannot be considered satisfactory, even if wrappers are easy to define.. One may thus want to look for a wrapping language over document trees that (i) has a solid and well understood theoretical foundation, (ii) provides a good trade-off between complexity and the number of practical wrappers that can be expressed, (iii) is easy to use as a wrapper programming language, and (iv) is suitable for being incorporated into visual tools, since ideally all constructs of a wrapping language can be realized through corresponding visual primitives.. This article exhibits and studies such languages. It is understood in the literature that the scope of wrapping is a conceptually limited one. Information systems architectures that employ wrapping usually consist of at least two layers, a lower one that is restricted to extracting relevant data from data sources and making them available in a coherent representation using the data model supported by the higher layer, and a higher layer in which data transformation and integration tasks are performed which are necessary to fuse syntactically coherent data from distinct sources in a semantically coherent manner. With the term wrapping, we refer to the lower, syntactic integration layer. The higher, semantic integration layer is not topic of this article. Therefore, a wrapper is assumed to extract relevant data from a possibly poorly structured source and to put it into the desired representation formalism by applying a number of transformational changes close to the minimum possible. A wrapping language that permits arbitrary data transformations may be considered overkill.. The core notion that we base our wrapping approach on is that of an information extraction function, which takes a labeled unranked tree (representing a Web document) and returns a subset of its nodes. In the context of the present article, a wrapper is a program which implements one or several such functions, and thereby assigns unary predicates to document tree nodes. Based on these predicate assignments and the structure of the input tree, a new tree can be computed as the result of the information extraction process in a natural way, along the lines of the input tree but using the new labels and omitting nodes that have not been relabeled.. That way, we can take a tree, relabel its nodes, and declare some of them as irrelevant, but we cannot significantly transform its original structure. This coincides with the intuition that a wrapper may change the presentation of relevant information, its packaging or data model (which does not apply in the case of Web wrapping), but does not handle substantial data transformation tasks. We believe that this captures exactly the essence of wrapping.. We propose unary queries in monadic second-order logic (MSO) over unranked trees as an expressiveness yardstick for information extraction functions. MSO over trees is well-understood theory-wise [Thatcher and Wright 1968; Doner 1970; Courcelle 1990; Flum et al. 2001 ] (see also Thomas [1990 Thomas [ , 1997 ) and quite expressive. The MSO query evaluation problem is PSPACE-complete (combined complexity). The parameter of most significant influence in query evaluation is of course the size of the data. Unary MSO queries can be evaluated in linear time with respect to the sizes of the input trees [Flum et al. 2001; Courcelle 1990 ] using techniques that, unfortunately, have nonelementary complexity in terms of the size of the MSO query.. 2 Thus-even when assuming the size of a wrapper program (as a set of MSO formulae) to be small-we cannot accord satisfaction of requirement (ii). Moreover, MSO does not satisfy requirements (iii) and (iv): It is neither easy to use as a wrapping language nor does it lend itself to visual specification.. Presently, only two formalisms are known that precisely capture the unary MSO queries over trees yet are computationally cheaper to process, query automata [Neven and Schwentick 2002] , a form of deterministic two-way tree automata with a selection function, and Boolean attribute grammars [Neven and van den Bussche 2002] . At least the latter formalism satisfies requirement (ii)-Boolean attribute grammars can be evaluated efficiently both in terms of the size of the data and the query. However, we think that neither satisfies the requirements (iii) or (iv).. The main task of practical Web information extraction is the detection and extraction of interesting "objects" from a Web document. Modeling such objects in a wrapper often only requires a small fraction of the intuitive "complexity" of the full documents to be wrapped. However, both query automata and attribute grammars require to model the entire source documents, which may be substantially more cumbersome and work-intensive than just describing the objects of interest. Such a monolithic approach is very brittle in real-world applications where no full model of the source documents is available or their layouts change frequently. In contrast, all implemented practical systems for tree-based wrapping that we are aware of [Liu et al. 2000; Sahuguet and Azavant 2001; Baumgartner et al. 2001b ] are based on wrapping languages that allow to specify the objects of interest without requiring to model the entire source documents. We studied the expressiveness and complexity of monadic datalog over trees and the core fragment of its close relative, the practical wrapper programming language Elog. We showed that the expressive power of both languages is precisely that of the unary MSO queries. As a significant by-product which may be useful in future investigations, we discovered a simple normal form for monadic datalog over trees, TMNF, to which every program can be translated in linear time. In summary, we have studied a significant new practical application of logic (programming) to information systems from a theoretical perspective. The database programming language datalog, which has received considerable attention from the database theory community over many years (see, e.g., Abiteboul et al. [1995] ) but has ultimately failed to attract a large following in database practice, might thus experience a notable "rebirth" in the context of trees and the Web. Indeed, for datalog 12 Full Elog supports Web crawling, stratified negation, so-called distance tolerances in "before" and "after" atoms, and tree region extraction, all features missing from the fragments discussed here. Presenting these features in detail is beyond the scope of this article, but a detailed overview of the full Elog language is given in Baumgartner et al. [2001b Baumgartner et al. [ , 2001a . as a framework for selecting nodes from trees, the situation is substantially different from the general case of full datalog on arbitrary databases. Monadic datalog over trees has very low evaluation complexity, programs have a simple normal form, so rules never have to be long or intricate, and various automata-theoretic, languagetheoretic, and logical techniques exist for evaluating programs or optimizing them which are not available for full datalog.. As a final remark, monadic datalog also has applications in querying XML and checking the conformance of XML documents to DTD's and regular tree languages. Indeed, Core XPath , the logical core fragment of the popular XPath language, can be mapped efficiently to monadic datalog Frick et al. 2003 ] and thus inherits its very favorable worst-case evaluation complexity bounds.

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Mixed-order compositing for 3D paintings We present a method for rendering 3D paintings by compositing brush strokes embedded in space. The challenge in compositing 3D brush strokes is reconciling conflicts between their z-order in 3D and the order in which the strokes were painted, while maintaining temporal and spatial coherence. Our algorithm smoothly transitions between compositing closer strokes over those farther away and compositing strokes painted later over those painted earlier. It is efficient, running in O(n log n) time, and simple to implement. We demonstrate its effectiveness on a variety of 3D paintings. Traditional 2D painting techniques and digital 2D painting systems provide an artist with a lot of expressive freedom in the creation of a painting, allowing a wide range of styles. Translating this freedom into 3D so that paintings can be viewed from multiple angles has been a research challenge for many years. Meier [1996] first proposed generating brush strokes attached to 3D objects. Other systems rely more on the artist. For example, Disney's Deep Canvas [Katanics and Lappas 2003] and, most recently, OverCoat [Schmid et al. 2011] , present the artist with a 3D canvas that allows him or her to place stylized paint strokes in space based on 3D proxy geometry. In this paper, we refer to a collection of brush strokes embedded in space as a 3D painting (Figure 1 ).. A 3D painting system renders the scene by projecting each brush stroke onto the current view plane and rasterizing it as one or more fragments for every pixel that the stroke overlaps. This rendering method exposes a technical dilemma about the order in which the fragments should be composited. In the 2D painting metaphor, when the artist places a new paint stroke, it obscures all previous paint strokes that it overlaps. Such behavior is achieved by compositing in stroke order. From a 3D point of view, however, strokes that are closer to the viewer should obscure those that are farther away, which amounts to compositing in depth order. Compositing purely in stroke order negates much of the benefit of 3D painting, as the sense of tangible objects is lost when the view is changed. Compositing purely in depth order, on the other hand, leads to Zfighting, precluding the artist from painting over existing strokes, Figure 1 : A 3D painting, consisting of brush strokes embedded in space, composited using our method. c Disney Enterprises, Inc.. and thus ignores an important part of the 2D painting metaphor. This problem dates back to Meier's work [1996] and is illustrated in Figure 2 . Katanics and Lappas [2003] articulated the desire for mixed-order compositing: fragments that, in the artist's mind, belong on the same surface should be composited in stroke order, while those that belong on different surfaces should be composited in depth order. Unfortunately, assigning each fragment to a specific surface is often impossible: the stroke that generated the fragment may span several surfaces, may self-occlude, or may not even conform to a surface at all. The guideline Deep Canvas adopts is therefore to choose the appropriate ordering based on a depth tolerance d: fragments whose depths are within d of each other are assumed to lie on the same surface and composited in stroke order, but fragments that are farther apart are composited in depth order.. In this work, we formalize this idea for the first time. We state the requirements for compositing order and temporal coherence as four properties, which a mixed-order compositing function must satisfy (Section 3.2). We discuss the ways in which existing solutions fail to satisfy one or more of these properties (Section 3.3) and describe the resulting artifacts. We design a function that does satisfy all four properties (Section 3.4) and show how to compute it efficiently (Section 3.5). We present renderings produced by this method and discuss limitations and future extensions (Section 4). 3D paintings hold great potential as an expressive medium that allows an artist to make use of 3D structure without being bound by limitations of the traditional 3D pipeline. A sound rendering and compositing method is necessary for 3D paintings, especially animated scenes, to gain wider use and realize this potential. We have presented such a method and proved that it has several desirable properties. We have also presented an efficient algorithm to compute it, and demonstrated its effectiveness on both synthetic and real examples. One of the first uses of paint strokes as rendering primitives was seen in Haeberli's "Paint By Numbers" [1990] , which augments brush strokes indicated by the user with additional information, such as color or direction, from underlying photographs or rendered images. This concept was later extended to arrange and render brush strokes automatically based on photographs or video, and has lead to excellent results [Litwinowicz 1997; Hertzmann 1998; Lu et al. 2010] . Because such methods work entirely in image space, they do not suffer from visibility ambiguities during rendering.. Instead of images, 3D scenes can also be used as the basis to generate brush strokes. In Meier's painterly rendering system [1996] , brush strokes are seeded by particles that are placed on 3D models. Color, direction, and size of the brush strokes are determined by separate reference images that are obtained by rendering the 3D models using specialized shaders. To obtain a painterly appearance, the brush strokes are rendered in image space after projection to the screen plane. This rendering concept was refined by Disney's Deep Canvas 3D painting system [Daniels et al. 2001; Katanics and Lappas 2003] , in which brush strokes were manually applied in different views of a scene and immediately projected onto the underlying 3D geometry in a parametric form. Recently, the concept of stroke projection has been generalized to a more flexible method of embedding paint strokes in space that does not restrict the stroke placement to 3D surfaces [Schmid et al. 2011] . All of these methods share the need for mixed-order compositing, as described in the introduction, but they use different ad-hoc solutions, which we discuss in Section 3.3.. The "WYSIWYG NPR" system presented by Kalnins and colleagues [2002] also allows the user to project paint strokes onto 3D models, but they use discrete visibility testing instead of depth ordering, which can lead to popping and is restricted to strokes which adhere strictly to 3D surfaces. Keefe and colleagues [2001] used a virtual-reality environment to let the artist paint directly in space. In their system, paint strokes are represented by standard 3D primitives, which can be composited in strict depth order, but cannot easily accomodate a more painterly aesthetic.. Digital compositing with the alpha channel was invented by Catmull and Smith [Smith 1995] . Wallace [1981] wrote down the equation for the over operator, while Porter and Duff [1984] introduced premultiplied alpha and described the algebra of compositing. Because the over operator is not commutative, the order in which fragments are composited matters, leading to sorting algorithms for real-time rendering [Mammen 1989 ] and techniques for allowing the user explicit control over the order [McCann and Pollard 2009] .. Conflicting orders of compositing have recently been considered by Bruckner et al. [2010] for illustrating 3D layers. Their goal is, in some sense, a transpose of ours: we aim to composite fragments close together in stroke order and fragments far apart in depth order, while they composite user-specified adjacent layers in depth order and the results in layer order. Their method works well for illustrative rendering and shares some technical similarity with ours. The problem they are solving is more restricted than ours: in their setting, the user specifies which layers are composited in which order and this order cannot change continuously, while our method needs to smoothly transition between compositing in depth order and in stroke order. Furthermore, their solution requires worst-case quadratic time in the number of layers (which roughly correspond to our fragments), while ours runs in O(n log n). For 3D paintings with hundreds or even thousands of fragments per pixel, a quadratic-time method is prohibitively expensive. We start by defining what properties a mixed-order compositing function needs to satisfy for pleasing animation results. We then de- scribe such a function and an algorithm that computes it efficiently.. In the supplemental material, we prove that our compositing function satisfies the desired properties. We now describe an algorithm to compute the function C efficiently in O(n log n) time and using O(n) memory. The high-level procedure is to explicitly compute S(z) in O(n log n) time and then define the replacement colors in linear time. Naïve algorithms for Figure 3 : The binary tree used to compute S(z). The leaves correspond to four fragments in this pixel. At the time instant shown, fragments 1 and 3 (with s1 = 3 and s3 = 2) are in the window. Suppose fragment 2 enters the window and s2 = 4. This change requires an update of the nodes t7, t3, and t1 for the root to have the correct new S(z). . The stroke order is z1, z3, z2. During the integration, the contribution of the interval I is added to the replacement colors of fragments z2 and z3. The vertical separation is used only to make the illustration less cluttered.. both of these tasks run in quadratic time because each distinct value of S can depend on all n fragments and each replacement color can depend on all Ω(n) distinct values of S. Our algorithm instead sweeps across depth and exploits the problem structure to compute values of S and replacement colors (c , α ) incrementally.. We start by using a sort to assign fragments distinct stroke numbers from 1 to n. As previously noted, S(z) only changes at zi + d/2 and zi − d/2, and therefore it only needs to be computed at these locations. At zi−d/2, S is modified to include the new fragment zi, and at zi + d/2, S changes to no longer include zi. To accomodate these events, we need a data structure that maintains a subset of the fragments and can add or remove a fragment from the subset efficiently. It also needs to be able to report the composite of this subset in stroke order. We use a complete binary tree with n leaves, each node of which stores a color and alpha, initially (0, 0). Leaf si of the tree stores either (0, 0) or (ci, αi), and each internal node stores the composite of its children in reverse order (because later strokes go on top). The root therefore stores the composite of all of the leaves of the tree in stroke order. Inserting or deleting a fragment can be achieved by changing the appropriate leaf from (0, 0) to (ci, αi) or vice versa and updating all of the nodes on the path to the root (Figure 3 ). These updates therefore run in O(log n) time.. Now that S(z) is known, we compute its integral over a window of size γd around each fragment (Figure 4) . Consider the union of the set of discontinuities of S and the points zi ± γd/2. This union par- titions the interval [z1 − γd/2, zn + γd/2] into at most 4n subintervals. Within such a subinterval I, S(z) is constant by construction. The set of fragments within γd/2 of z is also constant and contiguous, consisting of all fragments from zj to z j+k , for some j and k. The contribution of I to each fragment in this set is S(I)/γd times the length of I. Because k may be as large as n, adding this contribution to all fragments is too expensive. However, if we maintain the integrals as differences between adjacent fragments, (∆c i , ∆α i ) = (c i − c i−1 , α i − α i−1 ), we can add the contribution to (∆c j , ∆α j ) and subtract it from (∆c j+k+1 , ∆α j+k+1 ) in O(1) time. We process all 4n subintervals by sweeping over the discontinuities of S and the points zi ± γd/2 and incrementally maintaining j and k. Before doing the final composite, we compute (c i , α i ) from the deltas by computing the prefix sum.

O B O O O O O O O O O O O O B O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O B O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Endometriosis and infertility Abstract Endometriosis is a debilitating condition characterized by high recurrence rates. The etiology and pathogenesis remain unclear. Typically, endometriosis causes pain and infertility, although 20-25% of patients are asymptomatic. The principal aims of therapy include relief of symptoms, resolution of existing endometriotic implants, and prevention of new foci of ectopic endometrial tissue. Current therapeutic approaches are far from being curative; they focus on managing the clinical symptoms of the disease rather than fighting the disease. Specific combinations of medical, surgical, and psychological treatments can ameliorate the quality of life of women with endometriosis. The benefits of these treatments have not been entirely demonstrated, particularly in terms of expectations that women hold for their own lives. Although theoretically advantageous, there is no evidence that a combination medical-surgical treatment significantly enhances fertility, and it may unnecessarily delay further fertility therapy. Randomized controlled trials are required to demonstrate the efficacy of different treatments. Endometriosis is defined as the presence of endometriallike tissue (glands and stroma) outside the uterus, which induces a chronic inflammatory reaction, scar tissue, and adhesions that may distort a woman's pelvic anatomy [1] . Endometriosis is primarily found in young women, but its occurrence is not related to ethnic or social group distinctions. Patients with endometriosis mainly complain of pelvic pain, dysmenorrhea, and dyspareunia [2] . The associated symptoms can impact the patient's general physical, mental, and social well being [1] . osis are infertile [4] . More recent data indicate that the incidence of endometriosis has not increased in the last 30 years and remains at 2.37-2.49/1000/y, which equates to an approximate prevalence of 6-8% [5] .. To date, it has not been possible to determine whether a medical approach is less expensive than a surgical approach in patients with chronic pelvic pain. Also, data is lacking regarding the cost of treating endometriosis in infertile patients [6] .. On May 10th, 2007, the Public Health Executive Agency of the European Union announced that a €296,000 grant was awarded to a European coalition of universities and patient support organizations to improve the awareness of endometriosis in Europe.

B O B O B O O O O O O O O O O O O O O O O B O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O


On the diameter and girth of zero-divisor graphs of posets In this paper, we deal with zero-divisor graphs of posets. We prove that the diameter of such a graph is either 1, 2 or 3 while its girth is either 3, 4 or ∞. We also characterize zero-divisor graphs of posets in terms of their diameter and girth. Algebraic combinatorics is an area of mathematics that employs methods of abstract algebra in various combinatorial contexts and vice versa. Associating a graph to an algebraic structure is a research subject in this area and has attracted considerable attention. In fact, the research in this subject aims at exposing the relationship between algebra and graph theory and at advancing the application of one to the other. In 1988, Beck [3] introduced the idea of a zero-divisor graph of a commutative ring R with identity. He defined Γ 0 (R) to be the graph whose vertices are elements of R and in which two vertices x and y are adjacent if and only if xy = 0. He was mostly concerned with coloring of Γ 0 (R). Let χ(R) and ω(R) denote the chromatic number and the clique number of Γ 0 (R), respectively. Beck conjectured that χ(R) = ω(R). Such graphs are called weakly perfect graphs. This investigation of coloring of a commutative ring was then continued by Anderson and Naseer in [1] . They gave a counterexample for the above conjecture of Beck. A different method of associating a zero-divisor graph to a commutative ring R was proposed by Anderson and Livingston in [2] . They believed that this better illustrated the zero-divisor structure of the ring. They defined Γ(R) to be the graph whose vertices are nonzero zero-divisors of R and in which two vertices x and y are adjacent if and only if xy = 0. This graph is defined slightly different from the graph introduced by Beck who took the set of vertices to be the whole of R.. In the past decade, many authors have studied zero-divisor graphs of rings or other graphs associated to the other algebraic structures. For instance, Nimbhorkar et al. [14] have shown that Beck's conjecture holds true for commutative semigroups with zero in which each element is idempotent. These semigroups are called meetsemilattices. Recently, Halaš and Länger [9] have introduced the zero-divisor graphs of qosets and they have shown that Beck's conjecture holds true for these graphs. Also, Halaš and Jukl [8] introduced the zero-divisor graphs of posets and answered affirmatively to the Beck's conjecture. The study of the zero-divisor graphs of posets was then continued by Xue and Liu in [15] . More recently, a different method of associating a zero-divisor graph to a poset P was proposed by Lu and Wu in [13] . The graph defined by them is slightly different from the one defined in [8, 15] , where the vertex-set of the graph consists of all the elements of P . The vertex-set of the graph defined in [13] consists of all nonzero zero-divisors of P .. In this paper, we deal with zero-divisor graphs of posets based on the terminology of [13] . We prove that the diameter of such a graph is either 1, 2 or 3 while its girth is either 3, 4 or ∞. We also characterize zero-divisor graphs of posets in terms of their diameter and girth.

O O B O B O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O B O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O B O B


On the efficient evaluation of probabilistic similarity functions for image retrieval Abstract-Probabilistic approaches are a promising solution to the image retrieval problem that, when compared to standard retrieval methods, can lead to a significant gain in retrieval accuracy. However, this occurs at the cost of a significant increase in computational complexity. In fact, closed-form solutions for probabilistic retrieval are currently available only for simple probabilistic models such as the Gaussian or the histogram. We analyze the case of mixture densities and exploit the asymptotic equivalence between likelihood and Kullback-Leibler (KL) divergence to derive solutions for these models. In particular, 1) we show that the divergence can be computed exactly for vector quantizers (VQs) and 2) has an approximate solution for Gauss mixtures (GMs) that, in high-dimensional feature spaces, introduces no significant degradation of the resulting similarity judgments. In both cases, the new solutions have closed-form and computational complexity equivalent to that of standard retrieval approaches.Index Terms-Bayes classifier, Gauss mixture (GM), image databases, Kullback-Leibler (KL) divergence, maximum probability (MAP) similarity, probabilistic image retrieval, vector quantizer (VQ). Probabilistic solutions have shown great promise for the CBIR problem, but have traditionally been difficult to deploy in practice due to the complexity of the MAP similarity function. In this work, we have shown that this similarity function can be computed efficiently when VQs are used as models for the pdfs of the image features. We have also argued that in the more general GM case, the MAP function can be well approximated by a closed-form expression of reduced complexity, which we denoted by ALA. The accuracy of this approximation increases with the dimension of the feature space in which similarity is computed. Experimental evaluation has shown that the combination of probabilistic retrieval (using either of these functions) with GMs can outperform retrieval techniques that are popular in the area of CBIR.. While the focus of this work has been in image retrieval, we believe that the conclusions will hold for any other databases containing signals characterized by high-dimensional features. This includes music, audio, video, and even signals that have traditionally not been considered in the database literature, such as those associated with DNA information. We also believe that the theoretical significance of the results here presented goes well beyond the information retrieval problem. Mixture models are widely used in statistical modeling and computing the KL divergence between them is a problem that appears frequently when they are employed. Currently, this implies the use of Monte Carlo procedures that are computationally expensive. The complexity can be overwhelming when this process has to be repeated within some other algorithm, e.g., expectation-maximization or inference algorithms for probabilistic networks [24] . We believe that the results presented in this work can dramatically improve the computational efficiency of such algorithms.

O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I B I B I I O O O O B I I B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Usability of overview-supported zooming on small screens with regard to individual differences in spatial ability While zoomable user interfaces can improve the usability of applications by easing data access, a drawback is that some users tend to become lost after they have zoomed in. Previous studies indicate that this effect could be related to individual differences in spatial ability. To overcome such orientation problems, many desktop applications feature an additional overview window showing a miniature of the entire information space. Small devices, however, have a very limited screen real estate and incorporating an overview window often means pruning the size of the detail view considerably. Given this context, we report the results of a user study in which 24 participants solved search tasks by using two zoomable scatterplot applications on a PDA -one of the applications featured an overview, the other relied solely on the detail view. In contrast to similar studies for desktop applications, there was no significant difference in user preference between the interfaces. On the other hand, participants solved search tasks faster without the overview. This indicates that, on small screens, a larger detail view can outweigh the benefits gained from an overview window. Individual differences in spatial ability did not have a significant effect on task-completion times although results suggest that participants with higher spatial ability were slowed down by the overview more than low spatial-ability users. This paper analyzes the usability of zoomable (ZUIs) and overview plus detail (o+d) interfaces on small screens, taking into account individual differences in spatial ability. There are two main objectives of this research. First, we wanted to explore how an overview affects user performance, satisfaction and interface preference, given a very limited screen real estate. The second objective was to investigate how users with different levels of spatial ability interact with interfaces that offer different amounts of overview information. The results obtained may support developers when designing interfaces for small devices. The second interface enhanced the detail view with a smaller overview window at the bottom of the screen (Figure 2a) . The size of the overview was chosen such that the same scatterplot scale intervals as in the detail view could be used, with the axes labels remaining legible. This resulted in a layout in which the detail view was 40 percent smaller than in the detail-only interface. Both windows were tightly coupled, i.e. performing an operation on one view immediately updated the other one. The overview featured a field-ofview box (yellow rectangle) denoting the clipping currently presented in the detail view. Items that were highlighted on the detail view appeared red on the overview. Users could either pan on the overview by dragging the field-of-view box, or jump to another position by tapping the overview window outside the box. The field-of-view box then automatically moved to the pen position. If users had previously retrieved a movie's textual representation on the detail view ( Figure 2b ), panning or jumping on the overview changed the zoom level from 40 to 32 such that the detail window switched back to the diagram view. Zooming on the overview was achieved by first tapping on the scale button and then drawing a new field-of-view box on the overview. The box had a fixed aspect ratio which was determined by the ratio of the views. By zooming on the overview, it was not possible to achieve a scale level of over 32. Hence, to retrieve an item's textual representation, users had to zoom on the detail view. In this paper we analyzed the usability of small-screen ZUIs with and without overview with respect to individual differences in spatial ability. In an experiment that involved searching a movie database on a PDA, we found that participants were significantly faster using a detail-only ZUI compared to an overview-supported ZUI. This indicates that, on small screens, a larger detail window can outweigh the benefits gained from an overview. For high-spatial users, we assume that the performance difference is also partly due to the rich navigation cues provided by scatterplot labels.. Since the overview may not offer much of an orientation benefit for those users, it thus became more of a hindrance. Low-spatial participants, on the other hand, were less affected by the overview. Their task-completion times for the overview interface turned out to be nearly equal to those for the detail-only. In this case, the overview may have actually supported the participants by preventing them from relying on their potentially incorrect mental model of the information space. However, the performance differences measured between the two user groups were not significant. We conjecture that this is mainly due to the rather small group size and cognitive homogeneity of our participants. For further research, we would recommend a broader testing approach as carried out, for example, by [24] . In that study, initially 74 individuals took the spatial-ability test. For the computer experiment, the researchers then selected 24 of the subjects who fell into the extremes of the range.. Unlike a similar study for desktop applications that had identified a strong user preference for o+d interfaces [15] , our experiment did not show a significant difference in preference between the two ZUIs. User statements suggest that not only the smaller detail view but also the difficulties experienced by the participants with zooming and panning in the overview led to a lower rating for the overview-supported interface. Interestingly, our results once again show that interface efficiency does not necessarily correlate with user satisfaction or preference.. Based on our findings, we recommend that overviews on small devices would be best used for information spaces without strong orientation cues. Moreover, designers must carefully consider the real estate trade-off as well as the increased level of visual and interaction complexity that an o+d interface means. ZUIs, on the other hand, have been found to be an intuitive and elegant solution for visualizing data on small screens. The following section describes the results of our study. We will first focus on the four hypotheses and then present some additional analysis. The following section summarizes relevant previous research on ZUIs, o+d interfaces and spatial ability. It also explains our motivation and design considerations for the experiment conducted.

O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O


Canonical processes of media production Creating compelling multimedia presentations is a complex task. It involves the capture of media assets, then editing and authoring these into one or more final presentations. Tools tend to concentrate on a single aspect to reduce the complexity of the interface. While these tools are tailored to support a specific task, very often there is no consideration for input requirements for the next tool down the line. Each tool has the potential for adding semantic annotations to the media asset, describing relevant aspects of the asset and why it is being used for a particular purpose. These annotations need to be included in the information handed on to the next tool.We specify inputs and outputs to a number of canonical processes we identify in multimedia production. We do not specify the intricate workings of the processes, but concentrate on the information flow between them. Our claim is that by specifying the inputs and outputs required for processes that occur in widely differing uses of media we can identify a small set of building blocks that can be supported in semantically aware media production tools. There is substantial support within the multimedia research community for the collection of machine-processable semantics during established media workflow practices [2, 3, 6, 8, 10 ]. An essential aspect of these approaches is that a media asset gains value by the inclusion of information about how or when it is captured or used. For example, metadata captured from a camera on pan and zoom information can be later used for the support of the editing process.. Though the suggested combination of description structures for data, metadata and work processes is promising, the suggested approaches share an essential flaw, namely that the descriptions are not sharable. The problem is that each approach provides an implicit model for exchanging information that serves the particular functionality and process flow addressed by a particular environment. The situation is similar to data formats with included metadata, such as the mov 1 or XMP 2 formats, where the combination of features hinders general exchange when the application does not support the features supported by the data format.. Our aim here is to establish clear interfaces for the information flow across processes between distinct production phases so that compatibility across systems from different providers can be achieved. We see this as a first step towards a longer term goal -namely, to provide agreed-upon descriptions for exchanging semantically annotated media assets among applications.. The processes should not be viewed as prepackaged, ready to be implemented by a programmer. Our goal is rather to analyse existing systems to identify functionality they provide. On the basis of the processes supported within the system to determine which outputs should be available from the system. In this sense, we hope that system creators will be open to providing the outputs we identify when the processes are supported within the system. We hope that in this way the multimedia community will be able to strengthen itself by providing not just single process tools, but, in the same way that the pipe 3 was so important in the evolution of UNIX, allow these to belong to a (global) suite of mix and match tool functionality.. To validate the model we need to describe a number of workflows in terms of the processes identified in the model and specify the inputs and outputs. Contributions in the workshop include descriptions of video production [9] and new media artwork [7] in terms of the model. The structure of the paper is as follows. We derive the requirements for describing a single process, then identify and describe a number of processes we see as being canonical to media production. The paper concludes with a discussion of the proposed model. We see this paper plus the accompanying process descriptions as an initial step towards the definition of data structures which can be used and accessed by different members of the multimedia community. In this paper we identify processes that we see as being fundamental to different applications of multimedia and wish to discuss them further during the workshop. Even though based on a small set of applications our investigation on the applicability of our canonical processes provided relevant insights for our hypothesis that real parity between tools for the various tools in multimedia production environments can only be achieved if we get a better understanding of the connection between processes.. The main outcome of our investigation is that, despite the large amount of instantiated annotations as well as media document structures during a production, our canonical processes can provide the means for easing the access to potentially relevant information. As the defined ID types are related to processes that in turn are associated with particular stages within a production workflow it is the IDs that facilitate, if known, the entry points to purpose driven exploration or manipulation of the material.. Another interesting finding is that the IDs not only work on this global level of workflows but also help to access more detail areas of content description, as being exemplified by the ontID, attID and annIDs. These provide a particular view on the material, without being able to clearly determining the full semantic meaning of the media asset. For that the associated annotation structure needs to be investigated. Their advantage is, however, that they act like a messenger in cell communication and thus trigger decisions about the path through the knowledge space that is generated in a production. All that works because there is a relation between production tasks and the complexity level of the annotation system, which the defined IDs exploit. Making those generally available will improve the compatibility across systems from different providers which supports the tendency of users to make use of tools that are crafted to give high quality support for the tasks they need to perform without losing the capability to access media assets from various sources.. The current stage of our investigation is just a first step towards this aimed for process fluidity. There are still a number of obstacles that need to be investigated.. In the processes described in the previous section we do not address the issue of manipulating a media asset in the form of changing the intrinsic content of it -as tools like Photoshop allow to do on images. The intention is rather that the descriptions be independent of data format and editing/authoring system. If an editing action on a media asset, medID, does take place then a new media asset is created with a new identity. The author and/or authoring system/editing suite may choose to select large numbers of the previously associated annotations and include these in a new compID. The problem here is, that some aspects of the established annotations up to that stage might still be valid and thus could be kept even for the new media asset. How this detection of static and changeable media semantics can be detected within annotations and hence be exploited remains to be investigated.. When we select media assets for archival, are we able to archive them in multiple archives and preserve the connection between the compIDs in different archives? A more preferred solution might be of having a single conceptual UID that is stored in a conceptual single archive, but is potentially available from different physical places. We do not go further into naming schemes here, and refer to the work on URIs, URLs and URNs [12] but are aware that this point needs further investigation... In the processes as presented, we have note addressed the complications of being able to annotate annotations. This is of course what one would like to do, but it is out of scope of this paper. An annotation can, just as a (docID), be treated as a "media asset" -i.e. something of undefined data format that does not change and can have semantic annotations associated with it.. Within the processes specified we have assumed that the compID is an atomic entity. In the hypertext literature, composite components also exist. These however are more associated with the document structure rather than the underlying semantic annotations associated with a media asset. Hyperlinks similarly remain in the realm of the document structure and not in the underlying semantic relations. (See [11] where this distinction is explored.). Outside the scope of the current discussion is the notion of interaction. For a film or a book there is no (systemprocessed) interaction. However, for an interactive media artwork or an informative hypermedia presentation (e.g. blood flow in the body) interaction is part of the expression of the message and needs to be incorporated in the presentation distributed to the end user. For example, in [7] , the interaction is specified as Event-Condition-Action rules. Further work is needed to integrate the processes relating to interaction in the process model.. Related to the problem of interactivity is the problem of perception. If we assume here that a piece, be it an interactive art performance or a film, is consumed and interpreted over time, then we have to cope with ongoing circles of applying the canonical processes on the material, including the mix of it with other media sources. At the moment we have some vague ideas about the semantic side effects here -not only with respect to the naming of our processes but also on the flexibility that is demanded by combining content descriptions. Our current understanding is that the differences between compIds and messIDs as described during the post-production phase of film production will play an essential role here. We assume that a large amount of additional annotation on an interpretation level will favour dominant relations of messID types where occasionally compID references need to be established to specify particular parts of an audio-visual product. Moreover, at this stage of interpretation, as well as for reuse processes we see the need for including additional information structures of relations, a point that is not at all addressed in this paper.

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