OpenRaiser/Intern-Atlas huggingface dataset:
Information flow modeling based on diffusion rate for prediction and ranking
Authors: Xiaodan Song, Yun Chi, Koji Hino, Belle L. Tseng
Venue: WWW
Year: 2007

Information flows in a network where individuals influence each other. The diffusion rate captures how efficiently the information can diffuse among the users in the network. We propose an information flow model that leverages diffusion rates for: (1) prediction . identify where information should flow to, and (2) ranking . identify who will most quickly receive the information. For prediction, we measure how likely information will propagate from a specific sender to a specific receiver during a certain time period. Accordingly a rate-based recommendation algorithm is proposed that predicts who will most likely receive the information during a limited time period. For ranking, we estimate the expected time for information diffusion to reach a specific user in a network. Subsequently, a DiffusionRank algorithm is proposed that ranks users based on how quickly information will flow to them. Experiments on two datasets demonstrate the effectiveness of the proposed algorithms to both improve the recommendation performance and rank users by the efficiency of information flow.
Generative models for name disambiguation
Authors: Yang Song, Jian Huang, Isaac G. Councill, Jia Li, C. Lee Giles
Venue: WWW
Year: 2007

Name ambiguity is a special case of identity uncertainty where one person can be referenced by multiple name variations in different situations or evenshare the same name with other people. In this paper, we present an efficient framework by using two novel topic-based models, extended from Probabilistic Latent Semantic Analysis (PLSA) and Latent Dirichlet Allocation (LDA). Our models explicitly introduce a new variable for persons and learn the distribution of topics with regard to persons and words. Experiments indicate that our approach consistently outperforms other unsupervised methods including spectral and DBSCAN clustering. Scalability is addressed by disambiguating authors in over 750,000 papers from the entire CiteSeer dataset.
Generating efficient labels to facilitate web accessibility
Authors: Leo Spalteholz, Kin Fun Li, Nigel Livingston
Venue: WWW
Year: 2007

For many users with a disability it can be difficult or impossible to use a computer mouse to navigate the web. An alternative way to select elements on a web page is the label typing approach, in which users select elements by typing part of the label. In most cases, these labels are specified by the page authors, but some selectable elements do not have an obvious textual description, thus requiring that a label be generated. The set of element labels on a web page must be both efficient to select by text input and meaningful to the user. This paper discusses our approach to this problem, using page structural analysis and user history to determine important elements of a page, and then matching this information with the efficiency model of the input device.
Internet-scale collection of human-reviewed data
Authors: Qi Su, Dmitry Pavlov, Jyh-Herng Chow, Wendell C. Baker
Venue: WWW
Year: 2007

Enterprise and web data processing and content aggregation systems often require extensive use of human-reviewed data (e.g. for training and monitoring machine learning-based applications). Today these needs are often met by in-house efforts or out-sourced offshore contracting. Emerging applications attempt to provide automated collection of human-reviewed data at Internet-scale. We conduct extensive experiments to study the effectiveness of one such application. We also study the feasibility of using Yahoo! Answers, a general question-answering forum, for human-reviewed data collection.
SCAN: a small-world structured p2p overlay for multi-dimensional queries
Authors: Xiaoping Sun
Venue: WWW
Year: 2007

This paper presents a structured P2P overlay SCAN that augments CAN overlay with long links based on Kleinberg's small-world model in a d-dimensional Cartesian space. The construction of long links does not require the estimate of network size. Queries in multi-dimensional data space can achieve O(log n) hops by equipping each node with O(log n) long links and O(d)short links.
SRing: a structured non dht p2p overlay supporting string range queries
Authors: Xiaoping Sun, Xue Chen
Venue: WWW
Year: 2007

This paper presents SRing, a structured non DHT P2P overlay that efficiently supports exact and range queries on multiple attribute values. In SRing, all attribute values are interpreted as strings formed by a base alphabet and are published in the lexicographical order. Two virtual rings are built: N-ring is built in a skip-list way for range partition and queries; D-ring is built in a small-world way for the construction of N-ring. A leave-and-join based load balancing method is used to balance range overload in the network with heterogeneous nodes.
Multiway SLCA-based keyword search in XML data
Authors: Chong Sun, Chee Yong Chan, Amit K. Goenka
Venue: WWW
Year: 2007

Keyword search for smallest lowest common ancestors (SLCAs)in XML data has recently been proposed as a meaningful way to identify interesting data nodes inXML data where their subtrees contain an input set of keywords. In this paper, we generalize this useful search paradigm to support keyword search beyond the traditional AND semantics to include both AND and OR boolean operators as well. We first analyze properties of the LCA computation and propose improved algorithms to solve the traditional keyword search problem (with only AND semantics). We then extend our approach to handle general keyword search involving combinations of AND and OR boolean operators. The effectiveness of our new algorithms is demonstrated with a comprehensive experimental performance study.
A large-scale study of robots.txt
Authors: Yang Sun, Ziming Zhuang, C. Lee Giles
Venue: WWW
Year: 2007

Search engines largely rely on Web robots to collect information from the Web. Due to the unregulated open-access nature of the Web, robot activities are extremely diverse. Such crawling activities can be regulated from the server side by deploying the Robots Exclusion Protocol in a file called robots.txt. Although it is not an enforcement standard, ethical robots (and many commercial) will follow the rules specified in robots.txt. With our focused crawler, we investigate 7,593 websites from education, government, news, and business domains. Five crawls have been conducted in succession to study the temporal changes. Through statistical analysis of the data, we present a survey of the usage of Web robots rules at the Web scale. The results also show that the usage of robots.txt has increased over time.
Multi-factor clustering for a marketplace search interface
Authors: Neel Sundaresan, Kavita Ganesan, Roopnath Grandhi
Venue: WWW
Year: 2007

Search engines provide a small window to the vast repository of data they index and against which they search. They try their best to return the documents that are of relevance to the user but often a large number of results may be returned. Users struggle to manage this vast result set looking for the items of interest. Clustering search results is one way of alleviating this navigational pain. In this paper we describe a clustering system that enables clustering search results in an online marketplace search system.
Designing efficient sampling techniques to detect webpage updates
Authors: Qingzhao Tan, Ziming Zhuang, Prasenjit Mitra, C. Lee Giles
Venue: WWW
Year: 2007

Due to resource constraints, Web archiving systems and search engines usually have difficulties keeping the entire local repository synchronized with the Web. We advance the state-of-art of the sampling-based synchronization techniques by answering a challenging question: Given a sampled webpage and its change status, which other webpages are also likely to change? We present a study of various downloading granularities and policies, and propose an adaptive model based on the update history and the popularity of the webpages. We run extensive experiments on a large dataset of approximately 300,000 webpages to demonstrate that it is most likely to find more updated webpages in the current or upper directories of the changed samples. Moreover, the adaptive strategies outperform the non-adaptive one in terms of detecting important changes.
A scalable application placement controller for enterprise data centers
Authors: Chunqiang Tang, Malgorzata Steinder, Mike Spreitzer, Giovanni Pacifici
Venue: WWW
Year: 2007

Given a set of machines and a set of Web applications with dynamically changing demands, an online application placement controller decides how many instances to run for each application and where to put them, while observing all kinds of resource constraints. This NP hard problem has real usage in commercial middleware products. Existing approximation algorithms for this problem can scale to at most a few hundred machines, and may produce placement solutions that are far from optimal when system resources are tight. In this paper, we propose a new algorithm that can produce within 30 seconds high-quality solutions for hard placement problems with thousands of machines and thousands of applications. This scalability is crucial for dynamic resource provisioning in large-scale enterprise data centers. Our algorithm allows multiple applications to share a single machine, and strives to maximize the total satisfied application demand, to minimize the number of application starts and stops, and to balance the load across machines. Compared with existing state-of-the-art algorithms, for systems with 100 machines or less, our algorithm is up to 134 times faster, reduces application starts and stops by up to 97%, and produces placement solutions that satisfy up to 25% more application demands. Our algorithm has been implemented and adopted in a leading commercial middleware product for managing the performance of Web applications.
EPCI: extracting potentially copyright infringement texts from the web
Authors: Takashi Tashiro, Takanori Ueda, Taisuke Hori, Yu Hirate, Hayato Yamana
Venue: WWW
Year: 2007

In this paper, we propose a new system extracting potentially copyright infringement texts from the Web, called EPCI. EPCI extracts them in the following way: (1) generating a set of queries based on a given copyright reserved seed-text, (2) putting every query to search engine API, (3) gathering the search result Web pages from high ranking until the similarity between the given seed-text and the search result pages becomes less than a given threshold value, and (4) merging all the gathered pages, then re-ranking them in the order of their similarity. Our experimental result using 40 seed-texts shows that EPCI is able to extract 132 potentially copyright infringement Web pages per a given copyright reserved seed-text with 94% precision in average.
Consistency-preserving caching of dynamic database content
Authors: Niraj Tolia, Mahadev Satyanarayanan
Venue: WWW
Year: 2007

With the growing use of dynamic web content generated from relational databases, traditional caching solutions for through put and latency improvements are ineffective. We describe a middleware layer called Ganesh that reduces the volume of data transmitted without semantic interpretation of queries or results. It achieves this reduction through the use of cryptographic hashing to detect similarities with previous results. These benefits do not require any compromise of the strict consistency semantics provided by the back-end database. Further, Ganesh does not require modifications to applications, web servers, or database servers, and works with closed-source applications and databases. Using two bench marks representative of dynamic web sites, measurements of our prototype show that it can increase end-to-end throughput by as much as two fold for non-data intensive applications and by as much as ten fold for dataintensive ones.
Learning information intent via observation
Authors: Anthony Tomasic, Isaac Simmons, John Zimmerman
Venue: WWW
Year: 2007

Users in an organization frequently request help by sending request messages to assistants that express information intent: an intention to update data in an information system. Human assistants spend a significant amount of time and effort processing these requests. For example, human resource assistants process requests to update personnel records, and executive assistants process requests to schedule conference rooms or to make travel reservations. To process the intent of a request, assistants read the request and then locate, complete, and submit a form that corresponds to the expressed intent. Automatically or semi-automatically processing the intent expressed in a request on behalf of an assistant would ease the mundane and repetitive nature of this kind of work.For a well-understood domain, a straightforward application of natural language processing techniques can be used to build an intelligent form interface to semi-automatically process information intent request messages. However, high performance parsers are based on machine learning algorithms that require a large corpus of examples that have been labeled by an expert. The generation of a labeled corpus of requests is a major barrier to the construction of a parser. In this paper, we investigate the construction of a natural language processing system and an intelligent form system that observes an assistant processing requests. The intelligent form system then generates a labeled training corpus by interpreting the observations. This paper reports on the measurement of the performance of the machine learning algorithms based on real data. The combination of observations, machine learning and interaction design produces an effective intelligent form interface based on natural language processing.
Adaptive faceted browser for navigation in open information spaces
Authors: Michal Tvarozek, Mária Bieliková
Venue: WWW
Year: 2007

Open information spaces have several unique characteristics such as their changeability, large size, complexity and diverse user base. These result in novel challenges during user navigation, information retrieval and data visualization in open information spaces.We propose a method of navigation in open information spaces based on an enhanced faceted browser with support for dynamic facet generation and adaptation based on user characteristics.
Semantic personalization of web portal contents
Authors: Christina Tziviskou, Marco Brambilla
Venue: WWW
Year: 2007

Enriching Web applications with personalized data is of major interest for facilitating the user access to the published contents, and therefore, for guaranteeing successful user navigation. We propose a conceptual model for extracting personalized recommendations based on user profiling, ontological domain models, and semantic reasoning. The approach offers a high-level representation of the designed application based on a domain-specific metamodel for Web applications called WebML.
Behavior based web page evaluation
Authors: Ganesan Velayathan, Seiji Yamada
Venue: WWW
Year: 2007

This paper describes our efforts to investigate factors in user's browsing behavior to automatically evaluate web pages that the user shows interest in. To evaluate web pages automatically, we developed a client-side logging/analyzing tool: the GINIS Framework. This work focuses primarily on client-side user behavior using a customized web browser and AJAX technologies. First, GINIS unobtrusively gathers logs of user behavior through the user.s natural interaction with the web browser. Then it analyses the logs and extracts effective rules to evaluate web pages using C4.5 machine learning system. Eventually, GINIS becomes able to automatically evaluate web pages using these learned rules.
Academic web search engine: generating a survey automatically
Authors: Ye Wang, Zhihua Geng, Sheng Huang, Xiaoling Wang, Aoying Zhou
Venue: WWW
Year: 2007

Given a document repository, search engine is very helpful to retrieve information. Currently, vertical search is a hot topic, and Google Scholar [4] is an example for academic search. However, most vertical search engines only return the flat ranked list without an efficient result exhibition for given users. We study this problem and designed a vertical search engine prototype Dolphin, where the flexible user-oriented templates can be defined and the survey-like results are presented according to the template.
A search-based Chinese word segmentation method
Authors: Xin-Jing Wang, Yong Qin, Wen Liu
Venue: WWW
Year: 2007

In this paper, we propose a novel Chinese word segmentation method which leverages the huge deposit of Web documents and search technology. It simultaneously solves ambiguous phrase boundary resolution and unknown word identification problems. Evaluations prove its effectiveness.
Measuring credibility of users in an e-learning environment
Authors: Wei Wei, Jimmy Ho-Man Lee, Irwin King
Venue: WWW
Year: 2007

Learning Villages (LV) is an E-learning platform for people's online discussions and frequently citing postings of one another. In this paper, we propose a novel method to rank credit authors in the LV system. We first propose a k-EACM graph to describe the article citation structure in the LV system. And then we build a weighted graph model k-UCM graph to reveal the implicit relationship between authors hidden behind the citations among their articles. Furthermore, we design a graph-based ranking algorithm, the Credit Author Ranking (CAR) algorithm, which can be applied to rank nodes in a graph with negative edges. Finally, we perform experimental evaluations by simulations. The results of evaluations illustrate that the proposed method works pretty well on ranking the credibility of users in the LV system.
SPath: a path language for XML schema
Authors: Erik Wilde, Felix Michel
Venue: WWW
Year: 2007

XML is increasingly being used as a typed data format, and therefore it becomes more important to gain access to the type system; very often this is an XML Schema. The XML Schema Path Language (SPath) presented in this paper provides access to XML Schema components by extending the well-known XPath language to also include the domain of XML Schemas. Using SPath, XML developers gain access to XML Schemas and thus can more easily develop software which is type- or schema-aware, and thus more robust.
XML-based XML schema access
Authors: Erik Wilde, Felix Michel
Venue: WWW
Year: 2007

XML Schema's abstract data model consists of components, which are the structures that eventually define a schema as a whole. XML Schema's XML syntax, on the other hand, is not a direct representation of the schema components, and it proves to be surprisingly hard to derive a schema's components from the XML syntax. The Schema Component XML Syntax (SCX) is a representation which attempts to map schema components as faithfully as possible to XML structures. SCX serves as the starting point for applications which need access to schema components and want to do so using standardized and widely available XML technologies.
Querying and maintaining a compact XML storage
Authors: Raymond K. Wong, Franky Lam, William M. Shui
Venue: WWW
Year: 2007

As XML database sizes grow, the amount of space used for storing the data and auxiliary data structures becomes a major factor in query and update performance. This paper presents a new storage scheme for XML data that supports all navigational operations in near constant time. In addition to supporting efficient queries, the space requirement of the proposed scheme is within a constant factor of the information theoretic minimum, while insertions and deletions can be performed in near constant time as well. As a result, the proposed structure features a small memory footprint that increases cache locality, whilst still supporting standard APIs, such as DOM, and necessary database operations, such as queries and updates, efficiently. Analysis and experiments show that the proposed structure is space and time efficient.
Mobile shopping assistant: integration of mobile applications and web services
Authors: Huaigu Wu, Yuri Natchetoi
Venue: WWW
Year: 2007

The goal of this poster is to describe our implementation of a newarchitecture enabling efficient integration between mobile phoneapplications and Web Services. Using this architecture, we haveimplemented a mobile shopping assistant described further. In orderto build this architecture, we designed an innovative XMLcompression mechanism to facilitate data exchange between mobilephones and Web Services. We also designed a smart connection managerto control asynchronous communication for all possible channels of amobile phone. In addition, we used diverse input modes in order toextend users' access to Web Services.
Web page classification with heterogeneous data fusion
Authors: Zenglin Xu, Irwin King, Michael R. Lyu
Venue: WWW
Year: 2007

Web pages are more than text and they contain much contextual and structural information, e.g., the title, the meta data, the anchor text,etc., each of which can be seen as a data source or are presentation. Due to the different dimensionality and different representing forms of these heterogeneous data sources, simply putting them together would not greatly enhance the classification performance. We observe that via a kernel function, different dimensions and types of data sources can be represented into acommon format of kernel matrix, which can be seen as a generalized similarity measure between a pair of web pages. In this sense, a kernel learning approach is employed to fuse these heterogeneous data sources. The experimental results on a collection of the ODP database validate the advantages of the proposed method over traditional methods based on any single data source and the uniformly weighted combination of them.
Privacy-enhancing personalized web search
Authors: Yabo Xu, Ke Wang, Benyu Zhang, Zheng Chen
Venue: WWW
Year: 2007

Personalized web search is a promising way to improve search quality by customizing search results for people with individual information goals. However, users are uncomfortable with exposing private preference information to search engines. On the other hand, privacy is not absolute, and often can be compromised if there is a gain in service or profitability to the user. Thus, a balance must be struck between search quality and privacy protection. This paper presents a scalable way for users to automatically build rich user profiles. These profiles summarize a user.s interests into a hierarchical organization according to specific interests. Two parameters for specifying privacy requirements are proposed to help the user to choose the content and degree of detail of the profile information that is exposed to the search engine. Experiments showed that the user profile improved search quality when compared to standard MSN rankings. More importantly, results verified our hypothesis that a significant improvement on search quality can be achieved by only sharing some higher-level user profile information, which is potentially less sensitive than detailed personal information.
First-order focused crawling
Authors: Qingyang Xu, Wanli Zuo
Venue: WWW
Year: 2007

This paper reports a new general framework of focused web crawling based on "relational subgroup discovery". Predicates are used explicitly to represent the relevance clues of those unvisited pages in the crawl frontier, and then first-order classification rules are induced using subgroup discovery technique. The learned relational rules with sufficient support and confidence will guide the crawling process afterwards. We present the many interesting features of our proposed first-order focused crawler, together with preliminary promising experimental results.