OpenRaiser/Intern-Atlas huggingface dataset:
Sailer: an effective search engine for unified retrieval of heterogeneous xml and web documents
Authors: Guoliang Li, Jianhua Feng, Jianyong Wang, Xiaoming Song, Lizhu Zhou
Venue: WWW
Year: 2008

This paper studies the problem of unified ranked retrieval of heterogeneous XML documents and Web data. We propose an effective search engine called Sailer to adaptively and versatilely answer keyword queries over the heterogenous data. We model the Web pages and XML documents as graphs. We propose the concept of pivotal trees to effectively answer keyword queries and present an effective method to identify the top-k pivotal trees with the highest ranks from the graphs. Moreover, we propose effective indexes to facilitate the effective unified ranked retrieval. We have conducted an extensive experimental study using real datasets, and the experimental results show that Sailer achieves both high search efficiency and accuracy, and outperforms the existing approaches significantly.
Race: finding and ranking compact connected trees for keyword proximity search over xml documents
Authors: Guoliang Li, Jianhua Feng, Jianyong Wang, Bei Yu, Yukai He
Venue: WWW
Year: 2008

In this paper, we study the problem of keyword proximity search over XML documents and leverage the efficiency and effectiveness. We take the disjunctive semantics among input keywords into consideration and identify meaningful compact connected trees as the answers of keyword proximity queries. We introduce the notions of Compact Lowest Common Ancestor (CLCA) and Maximal CLCA (MCLCA) and propose Compact Connected Trees (CCTrees) and Maximal CCTrees (MCCTrees) to efficiently and effectively answer keyword queries. We propose a novel ranking mechanism, RACE, to Rank compAct Connected trEes, by taking into consideration both the structural similarity and the textual similarity. Our extensive experimental study shows that our method achieves both high search efficiency and effectiveness, and outperforms existing approaches significantly.
Pivotbrowser: a tag-space image searching prototype
Authors: Xiaoyan Li, Lidan Shou, Gang Chen, Xiaolong Zhang, Tianlei Hu, Jinxiang Dong
Venue: WWW
Year: 2008

We propose a novel iterative searching and refining prototype for tagged images. This prototype, named PivotBrowser, captures semantically similar tag sets in a structure called pivot. By constructing a pivot for a textual query, PivotBrowser first selects candidate images possibly relevant to the query. The tags contained in these candidate images are then selected in terms of their tag relevances to the pivot. The shortlisted tags are clustered and one of the tag clusters is used to select the results from the candidate images. Ranking of the images in each partition is based on their relevance to the tag cluster. With the guidance of the tag clusters presented, a user is able to perform searching and iterative query refinement.
Improving relevance judgment of web search results with image excerpts
Authors: Zhiwei Li, Shuming Shi, Lei Zhang
Venue: WWW
Year: 2008

Current web search engines return result pages containing mostly text summary even though the matched web pages may contain informative pictures. A text excerpt (i.e. snippet) is generated by selecting keywords around the matched query terms for each returned page to provide context for user's relevance judgment. However, in many scenarios, we found that the pictures in web pages, if selected properly, could be added into search result pages and provide richer contextual description because a picture is worth a thousand words. Such new summary is named as image excerpts. By well designed user study, we demonstrate image excerpts can help users make much quicker relevance judgment of search results for a wide range of query types. To implement this idea, we propose a practicable approach to automatically generate image excerpts in the result pages by considering the dominance of each picture in each web page and the relevance of the picture to the query. We also outline an efficient way to incorporate image excerpts in web search engines. Web search engines can adopt our approach by slightly modifying their index and inserting a few low cost operations in their workflow. Our experiments on a large web dataset indicate the performance of the proposed approach is very promising.
What do they think?: aggregating local views about news events and topics
Authors: Jiahui Liu, Larry Birnbaum
Venue: WWW
Year: 2008

The web has become an important medium for news delivery and consumption. Fresh content about a variety of topics and events is constantly being created and published on the web by many sources. As intuitively understood by readers, and studied in journalism, news articles produced by different social groups present different attitudes towards and interpretations of the same news issues. In this paper, we propose a new paradigm for aggregating news articles according to the news sources related to the stakeholders of the news issues. We implement this paradigm in a prototype system called LocalSavvy. The system provides users the capability to aggregate and browse various local views about the news issues in which they are interested.
A logical framework for modeling and reasoning about semantic web services contract
Authors: Hai Liu, Qing Li, Naijie Gu, An Liu
Venue: WWW
Year: 2008

In this paper, we incorporate concrete domain and action theory into a very expressive Description Logic (DL), called ALCQO. Notably, this extension can significantly augment the expressive power for modeling and reasoning about dynamic aspects of services contracting. Meanwhile, the original nature and advantages of classical DLs are also preserved to the extent possible. Categories and Subject Descriptors:
Asymmetrical query recommendation method based on bipartite network resource allocation
Authors: Zhiyuan Liu, Maosong Sun
Venue: WWW
Year: 2008

This paper presents a new query recommendation method that generates recommended query list by mining large-scale user logs. Starting from the user logs of click-through data, we construct a bipartite network where the nodes on one side correspond to unique queries, on the other side to unique URLs. Inspired by the bipartite network based resource allocation method, we try to extract the hidden information from the Query-URL bipartite network. The recommended queries generated by the method are asymmetrical which means two related queries may have different strength to recommend each other. To evaluate the method, we use one week user logs from Chinese search engine Sogou. The method is not only `content ignorant', but also can be easily implemented in a paralleled manner, which is feasible for commercial search engines to handle large scale user logs.
Efficiently finding web services using a clustering semantic approach
Authors: Jiangang Ma, Yanchun Zhang, Jing He
Venue: WWW
Year: 2008

Efficiently finding Web services on the Web is a challenging issue in service-oriented computing. Currently, UDDI is a standard for publishing and discovery of Web services, and UDDI registries also provide keyword searches for Web services. However, the search functionality is very simple and fails to account for relationships between Web services. Firstly, users are overwhelmed by the huge number of irrelevant returned services. Secondly, the intentions of users and the semantics in Web services are ignored. Inspired by the success of partitioning approach used in the database design, we used a novel clustering semantic algorithm to eliminate irrelevant services with respect to a query. Then we utilized Probabilistic Latent Semantic Analysis (PLSA), a machine learning method, to capture the semantics hidden behind the words in a query, and the descriptions in the services, so that service matching can be carried out at the concept level. This paper reports upon the preliminary experimental evaluation that shows improvements over recall and precision.
Temporal views over rdf data
Authors: Geetha Manjunath, R. Badrinath, Craig Sayers, K. S. Venugopal
Venue: WWW
Year: 2008

Supporting fast access to large RDF stores has been one of key challenges for enabling use of the Semantic Web in real-life applications, more so in sensor-based systems where large amounts of historic data needs to be stored. We propose a semantics-based temporal view mechanism that enables faster access to time-varying data by caching into memory only the required subset of RDF triples. We describe our experience of implementing such a framework in the context of a wide area network monitoring system. Our preliminary results show that our solution significantly improves client access time and scales well for moderate data sets.
Privacy-enhanced sharing of personal content on the web
Authors: Mohammad Mannan, Paul C. van Oorschot
Venue: WWW
Year: 2008

Publishing personal content on the web is gaining increased popularity with dramatic growth in social networking websites, and availability of cheap personal domain names and hosting services. Although the Internet enables easy publishing of any content intended to be generally accessible, restricting personal content to a selected group of contacts is more difficult. Social networking websites partially enable users to restrict access to a selected group of users of the same network by explicitly creating a "friends' list." While this limited restriction supports users' privacy on those (few) selected websites, personal websites must still largely be protected manually by sharing passwords or obscure links. Our focus is the general problem of privacy-enabled web content sharing from any user-chosen web server. By leveraging the existing "circle of trust" in popular Instant Messaging (IM) networks, we propose a scheme called IM-based Privacy-Enhanced Content Sharing (IMPECS) for personal web content sharing. IMPECS enables a publishing user's personal data to be accessible only to her IM contacts. A user can put her personal web page on any web server she wants (vs. being restricted to a specific social networking website), and maintain privacy of her content without requiring site-specific passwords. Our prototype of IMPECS required only minor modifications to an IM server, and PHP scripts on a web server. The general idea behind IMPECS extends beyond IM and IM circles of trust; any equivalent scheme, (ideally) containing pre-arranged groups, could similarly be leveraged.
Integrating the IAC neural network in ontology mapping
Authors: Ming Mao, Yefei Peng, Michael Spring
Venue: WWW
Year: 2008

Ontology mapping seeks to find semantic correspondences between similar elements of different ontologies. This paper proposes a neural network based approach to search for a global optimal solution that best satisfies ontology constraints. Experiments on OAEI benchmark tests show it dramatically improves the performance of preliminary mapping results.
Web page sectioning using regex-based template
Authors: Rupesh R. Mehta, Amit Madaan
Venue: WWW
Year: 2008

This work aims to provide a novel, site-specific web page segmentation and section importance detection algorithm, which leverages structural, content, and visual information. The structural and content information is leveraged via template, a generalized regular expression learnt over set of pages. The template along with visual information results into high sectioning accuracy. The experimental results demonstrate the effectiveness of the approach.
Detecting image spam using visual features and near duplicate detection
Authors: Bhaskar Mehta, Saurabh Nangia, Manish Gupta, Wolfgang Nejdl
Venue: WWW
Year: 2008

Email spam is a much studied topic, but even though current email spam detecting software has been gaining a competitive edge against text based email spam, new advances in spam generation have posed a new challenge: image-based spam. Image based spam is email which includes embedded images containing the spam messages, but in binary format. In this paper, we study the characteristics of image spam to propose two solutions for detecting image-based spam, while drawing a comparison with the existing techniques. The first solution, which uses the visual features for classification, offers an accuracy of about 98%, i.e. an improvement of at least 6% compared to existing solutions. SVMs (Support Vector Machines) are used to train classifiers using judiciously decided color, texture and shape features. The second solution offers a novel approach for near duplication detection in images. It involves clustering of image GMMs (Gaussian Mixture Models) based on the Agglomerative Information Bottleneck (AIB) principle, using Jensen-Shannon divergence (JS) as the distance measure.
Topic modeling with network regularization
Authors: Qiaozhu Mei, Deng Cai, Duo Zhang, ChengXiang Zhai
Venue: WWW
Year: 2008

In this paper, we formally define the problem of topic modeling with network structure (TMN). We propose a novel solution to this problem, which regularizes a statistical topic model with a harmonic regularizer based on a graph structure in the data. The proposed method bridges topic modeling and social network analysis, which leverages the power of both statistical topic models and discrete regularization. The output of this model well summarizes topics in text, maps a topic on the network, and discovers topical communities. With concrete selection of a topic model and a graph-based regularizer, our model can be applied to text mining problems such as author-topic analysis, community discovery, and spatial text mining. Empirical experiments on two different genres of data show that our approach is effective, which improves text-oriented methods as well as network-oriented methods. The proposed model is general; it can be applied to any text collections with a mixture of topics and an associated network structure.
Xml data dissemination using automata on top of structured overlay networks
Authors: Iris Miliaraki, Zoi Kaoudi, Manolis Koubarakis
Venue: WWW
Year: 2008

We present a novel approach for filtering XML documents using nondeterministic finite automata and distributed hash tables. Our approach differs architecturally from recent proposals that deal with distributed XML filtering; they assume an XML broker architecture, whereas our solution is built on top of distributed hash tables. The essence of our work is a distributed implementation of YFilter, a state-of-the-art automata-based XML filtering system on top of Chord. We experimentally evaluate our approach and demonstrate that our algorithms can scale to millions of XPath queries under various filtering scenarios, and also exhibit very good load balancing properties.
Sewnet -: a framework for creating services utilizing telecom functionality
Authors: Sumit Mittal, Dipanjan Chakraborty, Sunil Goyal, Sougata Mukherjea
Venue: WWW
Year: 2008

With Telecom market reaching saturation in many geographies and revenues from voice calls decreasing, Telecom operators are trying to identify new sources of revenue. For this purpose, these operators can take advantage of their core functionalities like Location, Call Control, etc. by exposing them as services to be composed by developers with third party offerings available over the Web. To hide the complexity of underlying Telecom protocols from application developers, the operators are steadily adopting Service Oriented Architecture (SOA) and reference standards like Parlay-X and IMS. However, a number of challenges still remain in rapid utilization of Telecom functionalities for creating new applications - existence of multiple protocols, different classes of developers, and the need to coordinate and manage usage of these functionalities. In this paper, we present SewNet, a framework for creating applications exploiting Telecom functionality exposed over a (converged) IP network. More specifically, SewNet a) provides an abstraction model for encapsulating invocation, coordination and enrichment of the Telecom functionalities, b) renders a service creation environment on top of this model, and c) caters to various different categories of developers. With the help of two use-case scenarios, we demonstrate how SewNet can create services utilizing rich Telecom functionality.
Using context to enable semantic mediation in web service communities
Authors: Michael Mrissa, Philippe Thiran, Chirine Ghedira, Djamal Benslimane, Zakaria Maamar
Venue: WWW
Year: 2008

The use of communities provides a scalable solution for gathering and managing functionally-equivalent Web services. In order to ensure single access to the community, a community uses a common interface that acts as a proxy and selects other Web services in the community. However, Web services adopt different semantics for representing the data they receive and send. These semantics must be adapted to conforming to the community semantics. In this paper, we present a solution to this problem. Our solution is based on the use of context in order to explicitly describe semantic discrepancies within a community. We rely on a semantic annotation of WSDL descriptions to describe the semantics attached to Web services, and we provide mediation mechanisms at the community level to handle semantic heterogeneities between Web services and the community. We validate our solution through implementation and experimentation over a test community and show the limitations of our approach.
WWW 2008 workshop: NLPIX2008 summary
Authors: Hiroshi Nakagawa, Kentaro Torisawa, Masaru Kitsuregawa
Venue: WWW
Year: 2008

The amount of information available on the Web has increased rapidly, reaching levels that few would ever have imagined possible. We live in what could be called the "information-explosion era," and this situation poses new problems for computer scientists. Users demand useful and reliable information from the Web in the shortest time possible, but the obstacles to fulfilling this demand are many including language barriers and the so-called "long tail." Even worse, users may provide only vague specifications of the information that they actually want, so that a more concrete specification must somehow be inferred by Web access tools. Natural language processing (NLP) is one of the key technologies for solving the above Web usability problems. Almost all the Web page provide with the essential information in the form of natural language texts, and the amount of these text information is huge. In order to offer solutions to these problems we must perform searching and extracting information from the Web texts using NLP technologies. The aim of this workshop: NLP Challenges in the Information Explosion Era (NLPIX 2008) is to bring researchers and practitioners together in order to discuss our most pressing needs with respect to accessing information on the Web, and to discuss new ideas in NLP technologies that might offer viable solutions for those issues.
Low-load server crawler: design and evaluation
Authors: Katsuko T. Nakahira, Tetsuya Hoshino, Yoshiki Mikami
Venue: WWW
Year: 2008

This paper proposes a method of crawling Web servers connected to the Internet without imposing a high processing load. We are using the crawler for a field survey of the digital divide, including the ability to connect to the network. Rather than employing normal Web 'page' crawling algorithm, which usually collect all pages found on the target server, we have developed 'server' crawling algorithm, which collect only minimum pages from the same server and achieved low-load and high-speed crawling of servers.
Dynamic cost-per-action mechanisms and applications to online advertising
Authors: Hamid Nazerzadeh, Amin Saberi, Rakesh Vohra
Venue: WWW
Year: 2008

We study the Cost-Per-Action or Cost-Per-Acquisition (CPA) charging scheme in online advertising. In this scheme, instead of paying per click, the advertisers pay only when a user takes a specific action (e.g. fills out a form) or completes a transaction on their websites.
Static query result caching revisited
Authors: Rifat Ozcan, Ismail Sengör Altingövde, Özgür Ulusoy
Venue: WWW
Year: 2008

Query result caching is an important mechanism for search engine efficiency. In this study, we first review several query features that are used to determine the contents of a static result cache. Next, we introduce a new feature that more accurately represents the popularity of a query by measuring the stability of query frequency over a set of time intervals. Experimental results show that this new feature achieves hit ratios better than those of the previously proposed features.
Scalable querying services over fuzzy ontologies
Authors: Jeff Z. Pan, Giorgos B. Stamou, Giorgos Stoilos, Stuart Taylor, Edward Thomas
Venue: WWW
Year: 2008

Fuzzy ontologies are envisioned to be useful in the Semantic Web. Existing fuzzy ontology reasoners are not scalable enough to handle the scale of data that the Web provides. In this paper, we propose a framework of fuzzy query languages for fuzzy ontologies, and present query answering algorithms for these query languages over fuzzy DL-Lite ontologies. Moreover, this paper reports on implementation of our approach in the fuzzy DL-Lite query engine in the ONTOSEARCH2 system and preliminary, but encouraging, benchmarking results. To the best of our knowledge, this is the first ever scalable query engine for fuzzy ontologies.
Web graph similarity for anomaly detection (poster)
Authors: Panagiotis Papadimitriou, Ali Dasdan, Hector Garcia-Molina
Venue: WWW
Year: 2008

Web graphs are approximate snapshots of the web, created by search engines. Their creation is an error-prone procedure that relies on the availability of Internet nodes and the faultless operation of multiple software and hardware units. Checking the validity of a web graph requires a notion of graph similarity. Web graph similarity helps measure the amount and significance of changes in consecutive web graphs. These measurements validate how well search engines acquire content from the web. In this paper we study five similarity schemes: three of them adapted from existing graph similarity measures and two adapted from well-known document and vector similarity methods. We compare and evaluate all five schemes using a sequence of web graphs for Yahoo! and study if the schemes can identify anomalies that may occur due to hardware or other problems.
Restful web services vs. "big"' web services: making the right architectural decision
Authors: Cesare Pautasso, Olaf Zimmermann, Frank Leymann
Venue: WWW
Year: 2008

Recent technology trends in the Web Services (WS) domain indicate that a solution eliminating the presumed complexity of the WS-* standards may be in sight: advocates of REpresentational State Transfer (REST) have come to believe that their ideas explaining why the World Wide Web works are just as applicable to solve enterprise application integration problems and to simplify the plumbing required to build service-oriented architectures. In this paper we objectify the WS-* vs. REST debate by giving a quantitative technical comparison based on architectural principles and decisions. We show that the two approaches differ in the number of architectural decisions that must be made and in the number of available alternatives. This discrepancy between freedom-from-choice and freedom-of-choice explains the complexity difference perceived. However, we also show that there are significant differences in the consequences of certain decisions in terms of resulting development and maintenance costs. Our comparison helps technical decision makers to assess the two integration styles and technologies more objectively and select the one that best fits their needs: REST is well suited for basic, ad hoc integration scenarios, WS-* is more flexible and addresses advanced quality of service requirements commonly occurring in enterprise computing.