OpenRaiser/Intern-Atlas huggingface dataset:
Web projections: learning from contextual subgraphs of the web
Authors: Jure Leskovec, Susan T. Dumais, Eric Horvitz
Venue: WWW
Year: 2007

Graphical relationships among Web pages have been exploited inmethods for ranking search results. To date, specific graphicalproperties have been used in these analyses. We introduce a WebProjection methodology that generalizes prior efforts of graphicalrelationships of the web in several ways. With the approach, wecreate subgraphs by projecting sets of pages and domains onto thelarger web graph, and then use machine learning to constructpredictive models that consider graphical properties as evidence. Wedescribe the method and then present experiments that illustrate theconstruction of predictive models of search result quality and userquery reformulation.
Hierarchical, perceptron-like learning for ontology-based information extraction
Authors: Yaoyong Li, Kalina Bontcheva
Venue: WWW
Year: 2007

Recent work on ontology-based Information Extraction (IE) has tried to make use of knowledge from the target ontology in order to improve semantic annotation results. However, very few approaches exploit the ontology structure itself, and those that do so, have some limitations. This paper introduces a hierarchical learning approach for IE, which uses the target ontology as an essential part of the extraction process, by taking into account the relations between concepts. The approach is evaluated on the largest available semantically annotated corpus. The results demonstrate clearly the benefits of using knowledge from the ontology as input to the information extraction process. We also demonstrate the advantages of our approach over other state-of-the-art learning systems on a commonly used benchmark dataset.
EOS: expertise oriented search using social networks
Authors: Juan-Zi Li, Jie Tang, Jing Zhang, Qiong Luo, Yunhao Liu, MingCai Hong
Venue: WWW
Year: 2007

In this paper, we present the design and implementation of our expertise oriented search system, EOS http://www.arnetminer.net. EOS is a researcher social network system. It has gathered information about a half-million computer science researchers from the Web and constructed a social network among the researchers through their co-authorship. In particular, the relationship in the social network information is used in both ranking experts for a given topic and searching for associations between researchers. Our experimental results demonstrate that the proposed methods for expert finding and association search in a social network are both more effective and efficient than the baseline methods.
A novel collaborative filtering-based framework for personalized services in m-commerce
Authors: Qiudan Li, Chunheng Wang, Guanggang Geng, Ruwei Dai
Venue: WWW
Year: 2007

With the rapid growth of wireless technologies and handheld devices, m-commerce is becoming a promising research area. Personalization is especially important to the success of m-commerce. This paper proposes a novel collaborative filtering-based framework for personalized services in m-commerce. The framework extends our previous work by using Online Analytical Processing (OLAP) to represent the relations among user, content and context information, and adopting a multi-dimensional collaborative filtering model to perform inference. It provides a powerful and well-founded mechanism to personalization for m-commerce. We implemented it in an existing m-commerce platform, and experimental results demonstrate its feasibility and correctness.
A novel clustering-based RSS aggregator
Authors: Xin Li, Jun Yan, Zhi-Hong Deng, Lei Ji, Weiguo Fan, Benyu Zhang, Zheng Chen
Venue: WWW
Year: 2007

In recent years, different commercial Weblog subscribing systems have been proposed to return stories from users. subscribed feeds. In this paper, we propose a novel clustering-based RSS aggregator called as RSS Clusgator System (RCS) for Weblog reading. Note that an RSS feed may have several different topics. A user may only be interested in a subset of these topics. In addition there could be many different stories from multiple RSS feeds, which discuss similar topic from different perspectives. A user may be interested in this topic but do not know how to collect all feeds related to this topic. In contrast to many previous works, we cluster all stories in RSS feeds into hierarchical structure to better serve the readers. Through this way, users can easily find all their interested stories. To make the system current, we propose a flexible time window for incremental clustering. RCS utilizes both link information and content information for efficient clustering. Experiments show the effectiveness of RCS.
Classifying web sites
Authors: Christoph Lindemann, Lars Littig
Venue: WWW
Year: 2007

In this paper, we present a novel method for the classification of Web sites. This method exploits both structure and content of Web sites in order to discern their functionality. It allows for distinguishing between eight of the most relevant functional classes of Web sites. We show that a pre-classification of Web sites utilizing structural properties considerably improves a subsequent textual classification with standard techniques. We evaluate this approach on a dataset comprising more than 16,000 Web sites with about 20 million crawled and 100 million known Web pages. Our approach achieves an accuracy of 92% for the coarse-grained classification of these Web sites.
Supporting end-users in the creation of dependable web clips
Authors: Sandeep Lingam, Sebastian G. Elbaum
Venue: WWW
Year: 2007

Web authoring environments enable end-users to create applications that integrate information from other web sources. Users can create web sites that include built-in components to dynamically incorporate, for example, weather information, stock-quotes, or the latest news from different web sources. Recent surveys conducted among end-users have indicated an increasing interest in creating such applications. Unfortunately, web authoring environments do not provide support beyond a limited set of built-in components. This work addresses this limitation by providing end-user support for "clipping" information from a target web site to incorporate it into the end-user site. The support consists of a mechanism to identify the target clipping with multiple markers to increase robustness, and a dynamic assessment of the retrieved information to quantify its reliability. The clipping approach has been integrated as a feature into a popular web authoring tool on which we present the results of two preliminary studies.
Automatic searching of tables in digital libraries
Authors: Ying Liu, Kun Bai, Prasenjit Mitra, C. Lee Giles
Venue: WWW
Year: 2007

Tables are ubiquitous. Unfortunately, no search engine supportstable search. In this paper, we propose a novel table specificsearching engine, TableSeer, to facilitate the table extracting, indexing, searching, and sharing. In addition, wepropose an extensive set of medium-independent metadata to precisely present tables. Given a query, TableSeer ranks the returned results using an innovative ranking algorithm - TableRank with a tailored vector space model and a novel term weightingscheme. Experimental results show that TableSeer outperforms existing search engines on table search. In addition, incorporating multiple weighting factors can significantly improve the ranking results.
Automatic search engine performance evaluation with click-through data analysis
Authors: Yiqun Liu, Yupeng Fu, Min Zhang, Shaoping Ma, Liyun Ru
Venue: WWW
Year: 2007

Performance evaluation is an important issue in Web search engine researches. Traditional evaluation methods rely on much human efforts and are therefore quite time-consuming. With click-through data analysis, we proposed an automatic search engine performance evaluation method. This method generates navigational type query topics and answers automatically based on search users. querying and clicking behavior. Experimental results based on a commercial Chinese search engine's user logs show that the automatically method gets a similar evaluation result with traditional assessor-based ones.
Compare&contrast: using the web to discover comparable cases for news stories
Authors: Jiahui Liu, Earl Wagner, Larry Birnbaum
Venue: WWW
Year: 2007

Comparing and contrasting is an important strategy people employ to understand new situations and create solutions for new problems. Similar events can provide hints for problem solving, as well as larger contexts for understanding the specific circumstances of an event. Lessons can leaned from past experience, insights can be gained about the new situation from familiar examples, and trends can be discovered among similar events. As the largest knowledge base for human beings, the Web provides both an opportunity and a challenge to discover comparable cases in order to facilitate situation analysis and problem solving. In this paper, we present Compare & Contrast, a system that uses the Web to discover comparable cases for news stories, documents about similar situations but involving distinct entities. The system analyzes a news story given by the user and builds a model of the story. With the story model, the system dynamically discovers entities comparable to the main entity in the original story and uses these comparable entities as seeds to retrieve web pages about comparable cases. The system is domain independent, does not require any domain-specific knowledge engineering efforts, and deals with the complexity of unstructured text and noise on the web in a robust way. We evaluated the system with an experiment on a collection of news articles and a user study.
A link classification based approach to website topic hierarchy generation
Authors: Nan Liu, Christopher C. Yang
Venue: WWW
Year: 2007

Hierarchical models are commonly used to organize a Website's content. A Website's content structure can be represented by a topic hierarchy, a directed tree rooted at a Website's homepage in which the vertices and edges correspond to Web pages and hyperlinks. In this work, we propose a new method for constructing the topic hierarchy of a Website. We model the Website's link structure using weighted directed graph, in which the edge weights are computed using a classifier that predicts if an edge connects a pair of nodes representing a topic and a sub-topic. We then pose the problem of building the topic hierarchy as finding the shortest-path tree and directed minimum spanning tree in the weighted graph. We've done extensive experiments using real Websites and obtained very promising results.
Towards service pool based approach for services discovery and subscription
Authors: Xuanzhe Liu, Li Zhou, Gang Huang, Hong Mei
Venue: WWW
Year: 2007

In current web service discovery and subscription, consumers must pay too much time on manually selection and cannot easily benefit from the wide QoS spectrum brought by the proliferating services. In our approach, we introduce the service pool as a "virtual service" grouping function identical services together and dispatching consumer requests to the proper service in terms of QoS requirements.
Deriving knowledge from figures for digital libraries
Authors: Xiaonan Lu, James Ze Wang, Prasenjit Mitra, C. Lee Giles
Venue: WWW
Year: 2007

Figures in digital documents contain important information. Current digital libraries do not summarize and index information available within figures for document retrieval. We present our system on automatic categorization of figures and extraction of data from 2-D plots. A machine-learning based method is used to categorize figures into a set of predefined types based on image features. An automated algorithm is designed to extract data values from solid line curves in 2-D plots. The semantic type of figures and extracted data values from 2-D plots can be integrated with textual information within documents to provide more effective document retrieval services for digital library users. Experimental evaluation has demonstrated that our system can produce results suitable for real-world use.
Answering relationship queries on the web
Authors: Gang Luo, Chunqiang Tang, Ying-li Tian
Venue: WWW
Year: 2007

Finding relationships between entities on the Web, e.g., the connections between different places or the commonalities of people, is a novel and challenging problem. Existing Web search engines excel in keyword matching and document ranking, but they cannot well handle many relationship queries. This paper proposes a new method for answering relationship queries on two entities. Our method first respectively retrieves the top Web pages for either entity from a Web search engine. It then matches these Web pages and generates an ordered list of Web page pairs. Each Web page pair consists of one Web page for either entity. The top ranked Web page pairs are likely to contain the relationships between the two entities. One main challenge in the ranking process is to effectively filter out the large amount of noise in the Web pages without losing much useful information. To achieve this, our method assigns appropriate weights to terms in Web pages and intelligently identifies the potential connecting terms that capture the relationships between the two entities. Only those top potential connecting terms with large weights are used to rank Web page pairs. Finally, the top ranked Web page pairs are presented to the searcher. For each such pair, the query terms and the top potential connecting terms are properly highlighted so that the relationships between the two entities can be easily identified. We implemented a prototype on top of the Google search engine and evaluated it under a wide variety of query scenarios. The experimental results show that our method is effective at finding important relationships with low overhead.
A probabilistic semantic approach for discovering web services
Authors: Jiangang Ma, Jinli Cao, Yanchun Zhang
Venue: WWW
Year: 2007

Service discovery is one of challenging issues in Service-Oriented computing. Currently, most of the existing service discovering and matching approaches are based on keywords-based strategy. However, this method is inefficient and time-consuming. In this paper, we present a novel approach for discovering web services. Based on the current dominating mechanisms of discovering and describing Web Services with UDDI and WSDL, the proposed approach utilizes Probabilistic Latent Semantic Analysis (PLSA) to capture semantic concepts hidden behind words in the query and advertisements in services so that services matching is expected to carry out at concept level. We also present related algorithms and preliminary experiments to evaluate the effectiveness of our approach.
Estimating the cardinality of RDF graph patterns
Authors: Angela Maduko, Kemafor Anyanwu, Amit P. Sheth, Paul Schliekelman
Venue: WWW
Year: 2007

Most RDF query languages allow for graph structure search through a conjunction of triples which is typically processed using join operations. A key factor in optimizing joins is determining the join order which depends on the expected cardinality of intermediate results. This work proposes a pattern-based summarization framework for estimating the cardinality of RDF graph patterns. We present experiments on real world and synthetic datasets which confirm the feasibility of our approach.
Towards environment generated media: object-participation-type weblog in home sensor network
Authors: Takuya Maekawa, Yutaka Yanagisawa, Takeshi Okadome
Venue: WWW
Year: 2007

The environment generated media (EGM) are defined here as being generated from a massive amount of and/or incomprehensible environmental data by compressing them into averages or representative values and/or by converting them into such user-friendly media as text, figures, charts, and animations. As an application of EGM, an object-participation-type weblog is introduced, where anthropomorphic indoor objects with sensor nodes post weblog entries and comments about what happened to them in a sensor networked environment.
Csurf: a context-driven non-visual web-browser
Authors: Jalal Mahmud, Yevgen Borodin, I. V. Ramakrishnan
Venue: WWW
Year: 2007

Web sites are designed for graphical mode of interaction. Sighted users can "cut to the chase" and quickly identify relevant information in Web pages. On the contrary, individuals with visual disabilities have to use screen-readers tobrowse the Web. As screen-readers process pages sequentially and read through everything, Web browsing can become strenuous and time-consuming. Although, the use ofshortcuts and searching offers some improvements, the problem still remains. In this paper, we address the problemof information overload in non-visual Web access using thenotion of context. Our prototype system, CSurf, embodyingour approach, provides the usual features of a screen-reader.However, when a user follows a link, CSurf captures thecontext of the link using a simple topic-boundary detectiontechnique, and uses it to identify relevant information onthe next page with the help of a Support Vector Machine, astatistical machine-learning model. Then, CSurf reads the Web page starting from the most relevant section, identifiedby the model. We conducted a series experiments to evaluate the performance of CSurf against the state-of-the-artscreen-reader, JAWS. Our results show that the use of context can potentially save browsing time and substantiallyimprove browsing experience of visually disabled people.
A fault model and mutation testing of access control policies
Authors: Evan Martin, Tao Xie
Venue: WWW
Year: 2007

To increase confidence in the correctness of specified policies, policy developers can conduct policy testing by supplying typical test inputs (requests) and subsequently checking test outputs (responses) against expected ones. Unfortunately, manual testing is tedious and few tools exist for automated testing of access control policies. We present a fault model for access control policies and a framework to explore it. The framework includes mutation operators used to implement the fault model, mutant generation, equivalentmutant detection, and mutant-killing determination. This framework allows us to investigate our fault model, evaluate coverage criteria for test generation and selection, and determine a relationship between structural coverage and fault-detection effectiveness. We have implemented the framework and applied it to various policies written in XACML. Our experimental results offer valuable insights into choosing mutation operators in mutation testing and choosing coverage criteria in test generation and selection.
A high-performance interpretive approach to schema-directed parsing
Authors: Morris Matsa, Eric Perkins, Abraham Heifets, Margaret Gaitatzes Kostoulas, Daniel Silva, Noah Mendelsohn, Michelle Leger
Venue: WWW
Year: 2007

XML delivers key advantages in interoperability due to its flexibility, expressiveness, and platform-neutrality. As XML has become a performance-critical aspect of the next generation of business computing infrastructure, however, it has become increasingly clear that XML parsing often carries a heavy performance penalty, and that current, widely-used parsing technologies are unable to meet the performance demands of an XML-based computing infrastructure. Several efforts have been made to address this performance gap through the use of grammar-based parser generation. While the performance of generated parsers has been significantly improved, adoption of the technology has been hindered by the complexity of compiling and deploying the generated parsers. Through careful analysis of the operations required for parsing and validation, we have devised a set of specialized byte codes, designed for the task of XML parsing and validation. These byte codes are designed to engender the benefits of fine-grained composition of parsing and validation that make existing compiled parsers fast, while being coarse-grained enough to minimize interpreter overhead. This technique of using an interpretive,validating parser balances the need for performance against the requirements of simple tooling and robust scalable infrastructure. Our approach is demonstrated with a specialized schema compiler, used to generate byte codes which in turn drive an interpretive parser. With almost as little tooling and deployment complexity as a traditional interpretive parser, the byte code-driven parser usually demonstrates performance within 20% of the fastest fully compiled solutions.
Compiling cryptographic protocols for deployment on the web
Authors: Jay A. McCarthy, Shriram Krishnamurthi, Joshua D. Guttman, John D. Ramsdell
Venue: WWW
Year: 2007

Cryptographic protocols are useful for trust engineering in Web transactions. The Cryptographic Protocol Programming Language (CPPL) provides a model wherein trust management annotations are attached to protocol actions, and are used to constrain the behavior of a protocol participant to be compatible with its own trust policy.
Optimal audio-visual representations for illiterate users of computers
Authors: Indrani Medhi, Archana Prasad, Kentaro Toyama
Venue: WWW
Year: 2007

We present research leading toward an understanding of the optimal audio-visual representation for illustrating concepts for illiterate and semi-literate users of computers. In our user study, which to our knowledge is the first of its kind, we presented to 200 illiterate subjects each of 13 different health symptoms in one representation randomly selected among the following ten: text, static drawings, staticphotographs, hand-drawn animations, and video, each with and without voice annotation. The goal was to see how comprehensible these representation types were for an illiterate audience. We used a methodology for generating each of the representations tested in a way that fairly stacks one representational type against the others.
Construction by linking: the linkbase method
Authors: Johannes Meinecke, Frederic Majer, Martin Gaedke
Venue: WWW
Year: 2007

The success of many innovative Web applications is not based on the content they produce -- but on how they combine and link existing content. Older Web Engineering methods lack flexibility in a sense that they rely strongly on a-priori knowledge of existing content structures and do not take into account initially unknown content sources. We propose the adoption of principles that are also found in Component-based Software Engineering, to assemble highly extensible solutions from reusable artifacts. The main contribution of our work is a support system, consisting of a central service that manages n:m relationships between arbitrary Web resources, and of Web application components that realize navigation, presentation, and interaction for the linked content.
Effort estimation: how valuable is it for a web company to use a cross-company data set, compared to using its own single-company data set?
Authors: Emilia Mendes, Sergio Di Martino, Filomena Ferrucci, Carmine Gravino
Venue: WWW
Year: 2007

Previous studies comparing the prediction accuracy of effort models built using Web cross- and single-company data sets have been inconclusive, and as such replicated studies are necessary to determine under what circumstances a company can place reliance on a cross-company effort model. This paper therefore replicates a previous study by investigating how successful a cross-company effort model is: i) to estimate effort for Web projects that belong to a single company and were not used to build the cross-company model; ii) compared to a single-company effort model. Our single-company data set had data on 15 Web projects from a single company and our cross-company data set had data on 68 Web projects from 25 different companies. The effort estimates used in our analysis were obtained by means of two effort estimation techniques, namely forward stepwise regression and case-based reasoning. Our results were similar to those from the replicated study, showing that predictions based on the single-company model were significantly more accurate than those based on the cross-company model.