OpenRaiser/Intern-Atlas huggingface dataset:
Rapid prototyping of semantic mash-ups through semantic web pipes
Authors: Danh Le Phuoc, Axel Polleres, Manfred Hauswirth, Giovanni Tummarello, Christian Morbidoni
Venue: WWW
Year: 2009

The use of RDF data published on the Web for applications is still a cumbersome and resource-intensive task due to the limited software support and the lack of standard programming paradigms to deal with everyday problems such as combination of RDF data from dierent sources, object identifier consolidation, ontology alignment and mediation, or plain querying and filtering tasks. In this paper we present a framework, Semantic Web Pipes, that supports fast implementation of Semantic data mash-ups while preserving desirable properties such as abstraction, encapsulation, component-orientation, code re-usability and maintainability which are common and well supported in other application areas.
Constructing folksonomies from user-specified relations on flickr
Authors: Anon Plangprasopchok, Kristina Lerman
Venue: WWW
Year: 2009

Automatic folksonomy construction from tags has attracted much attention recently. However, inferring hierarchical relations between concepts from tags has a drawback in that it is difficult to distinguish between more popular and more general concepts. Instead of tags we propose to use user-specified relations for learning folksonomy. We explore two statistical frameworks for aggregating many shallow individual hierarchies, expressed through the collection/set relations on the social photosharing site Flickr, into a common deeper folksonomy that reflects how a community organizes knowledge. Our approach addresses a number of challenges that arise while aggregating information from diverse users, namely noisy vocabulary, and variations in the granularity level of the concepts expressed. Our second contribution is a method for automatically evaluating learned folksonomy by comparing it to a reference taxonomy, e.g., the Web directory created by the Open Directory Project. Our empirical results suggest that user-specified relations are a good source of evidence for learning folksonomies.
Searching for events in the blogosphere
Authors: Manolis Platakis, Dimitrios Kotsakos, Dimitrios Gunopulos
Venue: WWW
Year: 2009

Over the last few years, blogs (web logs) have gained massive popularity and have become one of the most influential web social media in our times. Every blog post in the Blogosphere has a well defined timestamp, which is not taken into account by search engines. By conducting research regarding this feature of the Blogosphere, we can attempt to discover bursty terms and correlations between them during a time interval. We apply Kleinberg's automaton on extracted titles of blog posts to discover bursty terms, we introduce a novel representation of a term's burstiness evolution called State Series and we employ a Euclidean-based distance metric to discover potential correlations between terms without taking into account their context. We evaluate the results trying to match them with real life events. Finally, we propose some ideas for further evaluation techniques and future research in the field.
Deducing trip related information from flickr
Authors: Adrian Popescu, Gregory Grefenstette
Venue: WWW
Year: 2009

Uploading tourist photos is a popular activity on photo sharing platforms. These photographs and their associated metadata (tags, geo-tags, and temporal information) should be useful for mining information about the sites visited. However, user-supplied metadata are often noisy and efficient filtering methods are needed before extracting useful knowledge. We focus here on exploiting temporal information, associated with tourist sites that appear in Flickr. From automatically filtered sets of geo-tagged photos, we deduce answers to questions like "how long does it take to visit a tourist attraction?" or "what can I visit in one day in this city?" Our method is evaluated and validated by comparing the automatically obtained visit duration times to manual estimations.
Relationalizing RDF stores for tools reusability
Authors: Sunitha Ramanujam, Anubha Gupta, Latifur Khan, Steven Seida, Bhavani Thuraisingham
Venue: WWW
Year: 2009

The emergence of Semantic Web technologies and standards such as Resource Description Framework (RDF) has introduced novel data storage models such as the RDF Graph Model. In this paper, we present a research effort called R2D, which attempts to bridge the gap between RDF and RDBMS concepts by presenting a relational view of RDF data stores. Thus, R2D is essentially a relational wrapper around RDF stores that aims to make the variety of stable relational tools that are currently in the market available to RDF stores without data duplication and synchronization issues.
Bootstrapped extraction of class attributes
Authors: Joseph Reisinger, Marius Pasca
Venue: WWW
Year: 2009

As an alternative to previous studies on extracting class attributes from unstructured text, which consider either Web documents or query logs as the source of textual data, A bootstrapped method extracts class attributes simultaneously from both sources, using a small set of seed attributes. The method improves extraction precision and also improves attribute relevance across 40 test classes.
Bucefalo: a tool for intelligent search and filtering for web-based personal health records
Authors: Francisco P. Romero, Jesús Serrano-Guerrero, José Angel Olivas
Venue: WWW
Year: 2009

In this poster, a tool named BUCEFALO is presented. This tool is specially designed to improve the information retrieval tasks in web-based Personal Health Records (PHR). This tool implements semantic and multilingual query expansion techniques and information filtering algorithms in order to help users find the most valuable information about a specific clinical case. The filtering model is based on fuzzy prototypes based filtering, data quality measures, user profiles and healthcare ontologies. The first experimental results illustrate the feasibility of this tool.
Fast dynamic reranking in large graphs
Authors: Purnamrita Sarkar, Andrew W. Moore
Venue: WWW
Year: 2009

In this paper we consider the problem of re-ranking search results by incorporating user feedback. We present a graph theoretic measure for discriminating irrelevant results from relevant results using a few labeled examples provided by the user. The key intuition is that nodes relatively closer (in graph topology) to the relevant nodes than the irrelevant nodes are more likely to be relevant. We present a simple sampling algorithm to evaluate this measure at specific nodes of interest, and an efficient branch and bound algorithm to compute the top k nodes from the entire graph under this measure. On quantifiable prediction tasks the introduced measure outperforms other diffusion-based proximity measures which take only the positive relevance feedback into account. On the Entity-Relation graph built from the authors and papers of the entire DBLP citation corpus (1.4 million nodes and 2.2 million edges) our branch and bound algorithm takes about 1.5 seconds to retrieve the top 10 nodes w.r.t. this measure with 10 labeled nodes.
Crawling English-Japanese person-name transliterations from the web
Authors: Satoshi Sato
Venue: WWW
Year: 2009

Automatic compilation of lexicon is a dream of lexicon compilers as well as lexicon users. This paper proposes a system that crawls English-Japanese person-name transliterations from the Web, which works a back-end collector for automatic compilation of bilingual person-name lexicon. Our crawler collected 561K transliterations in five months. From them, an English-Japanese person-name lexicon with 406K entries has been compiled by an automatic post processing. This lexicon is much larger than other similar resources including English-Japanese lexicon of HeiNER obtained from Wikipedia.
Towards language-independent web genre detection
Authors: Philipp Scholl, Renato Domínguez García, Doreen Böhnstedt, Christoph Rensing, Ralf Steinmetz
Venue: WWW
Year: 2009

The term web genre denotes the type of a given web resource, in contrast to the topic of its content. In this research, we focus on recognizing the web genres blog, wiki and forum. We present a set of features that exploit the hierarchical structure of the web page's HTML mark-up and thus, in contrast to related approaches, do not depend on a linguistic analysis of the page's content. Our results show that it is possible to achieve a very good accuracy for a fully language independent detection of structured web genres.
Sitemaps: above and beyond the crawl of duty
Authors: Uri Schonfeld, Narayanan Shivakumar
Venue: WWW
Year: 2009

Comprehensive coverage of the public web is crucial to web search engines. Search engines use crawlers to retrieve pages and then discover new ones by extracting the pages' outgoing links. However, the set of pages reachable from the publicly linked web is estimated to be significantly smaller than the invisible web, the set of documents that have no incoming links and can only be retrieved through web applications and web forms. The Sitemaps protocol is a fast-growing web protocol supported jointly by major search engines to help content creators and search engines unlock this hidden data by making it available to search engines. In this paper, we perform a detailed study of how "classic" discovery crawling compares with Sitemaps, in key measures such as coverage and freshness over key representative websites as well as over billions of URLs seen at Google. We observe that Sitemaps and discovery crawling complement each other very well, and offer different tradeoffs.
Rare item detection in e-commerce site
Authors: Dan Shen, Xiaoyuan Wu, Alvaro Bolivar
Venue: WWW
Year: 2009

As the largest online marketplace in the world, eBay has a huge inventory where there are plenty of great rare items with potentially large, even rapturous buyers. These items are obscured in long tail of eBay item listing and hard to find through existing searching or browsing methods. It is observed that there are great rarity demands from users according to eBay query log. To keep up with the demands, the paper proposes a method to automatically detect rare items in eBay online listing. A large set of features relevant to the task are investigated to filter items and further measure item rareness. The experiments on the most rarity-demand-intensitive domains show that the method may effectively detect rare items (>90% precision).
Building term suggestion relational graphs from collective intelligence
Authors: Jyh-Ren Shieh, Yung-Huan Hsieh, Yang-Ting Yeh, Tse-Chung Su, Ching-Yung Lin, Ja-Ling Wu
Venue: WWW
Year: 2009

This paper proposes an effective approach to provide relevant search terms for conceptual Web search. 'Semantic Term Suggestion' function has been included so that users can find the most appropriate query term to what they really need. Conventional approaches for term suggestion involve extracting frequently occurring key terms from retrieved documents. They must deal with term extraction difficulties and interference from irrelevant documents. In this paper, we propose a semantic term suggestion function called Collective Intelligence based Term Suggestion (CITS). CITS provides a novel social-network based framework for relevant terms suggestion with a semantic graph of the search term without limiting to the specific query term. A visualization of semantic graph is presented to the users to help browsing search results from related terms in the semantic graph. The search results are ranked each time according to their relevance to the related terms in the entire query session. Comparing to two popular commercial search engines, a user study of 18 users on 50 search terms showed better user satisfactions and indicated the potential usefulness of proposed method in real-world search applications.
Ranking user-created contents by search user's inclination in online communities
Authors: Hyoseop Shin, Jeehoon Lee
Venue: WWW
Year: 2009

Searching posts effectively has become an important issue in large-scale online communities. Especially, if search users have different inclinations when they search posts, they have different kinds of posts in their minds. To address this problem, in this paper, we propose a scheme of ranking posts based on search users' inclination. User ranking score is employed to capture posts that are relevant to a specific user inclination. Specifically, we present a scheme to rank posts in terms of user expertise and popularity. Experimental results show that different user inclinations can produce quite different search results and the proposed scheme achieves about 70% accuracy.
A messaging API for inter-widgets communication
Authors: Stéphane Sire, Micaël Paquier, Alain Vagner, Jérôme Bogaerts
Venue: WWW
Year: 2009

Widget containers are used everywhere on the Web, for instance as customizable start pages to Web desktops. In this poster, we describe the extension of a widget container with an inter-widgets communication layer, as well as the subsequent application programming interfaces (APIs) added to the Widget object to support this feature. We present the benefits of a drag and drop facility within widgets and conclude by a call for standardization of inter-widgets communication on the Web.
Collective privacy management in social networks
Authors: Anna Cinzia Squicciarini, Mohamed Shehab, Federica Paci
Venue: WWW
Year: 2009

Social Networking is one of the major technological phenomena of the Web 2.0, with hundreds of millions of people participating. Social networks enable a form of self expression for users, and help them to socialize and share content with other users. In spite of the fact that content sharing represents one of the prominent features of existing Social Network sites, Social Networks yet do not support any mechanism for collaborative management of privacy settings for shared content. In this paper, we model the problem of collaborative enforcement of privacy policies on shared data by using game theory. In particular, we propose a solution that offers automated ways to share images based on an extended notion of content ownership. Building upon the Clarke-Tax mechanism, we describe a simple mechanism that promotes truthfulness, and that rewards users who promote co-ownership. We integrate our design with inference techniques that free the users from the burden of manually selecting privacy preferences for each picture. To the best of our knowledge this is the first time such a protection mechanism for Social Networking has been proposed. In the paper, we also show a proof-of-concept application, which we implemented in the context of Facebook, one of today’s most popular social networks. We show that supporting these type of solutions is not also feasible, but can be implemented through a minimal increase in overhead to end-users.
SOFIE: a self-organizing framework for information extraction
Authors: Fabian M. Suchanek, Mauro Sozio, Gerhard Weikum
Venue: WWW
Year: 2009

This paper presents SOFIE, a system for automated ontology extension. SOFIE can parse natural language documents, extract ontological facts from them and link the facts into an ontology. SOFIE uses logical reasoning on the existing knowledge and on the new knowledge in order to disambiguate words to their most probable meaning, to reason on the meaning of text patterns and to take into account world knowledge axioms. This allows SOFIE to check the plausibility of hypotheses and to avoid inconsistencies with the ontology. The framework of SOFIE unites the paradigms of pattern matching, word sense disambiguation and ontological reasoning in one unified model. Our experiments show that SOFIE delivers high-quality output, even from unstructured Internet documents.
Highly scalable web applications with zero-copy data transfer
Authors: Toyotaro Suzumura, Michiaki Tatsubori, Scott Trent, Akihiko Tozawa, Tamiya Onodera
Venue: WWW
Year: 2009

The performance of server-side applications is becoming increasingly important as more applications exploit the Web application model. Extensive work has been done to improve the performance of individual software components such as Web servers and programming language runtimes. This paper describes a novel approach to boost Web application performance by improving inter-process communication between a programming language runtime and Web server runtime. The approach reduces redundant processing for memory copying and the context switch overhead between user space and kernel space by exploiting the zero-copy data transfer methodology, such as the sendfile system call. In order to transparently utilize this optimization feature with existing Web applications, we propose enhancements of the PHP runtime, FastCGI protocol, and Web server. Our proposed approach achieves a 126% performance improvement with micro-benchmarks and a 44% performance improvement for a standard Web benchmark, SPECweb2005.
HTML templates that fly: a template engine approach to automated offloading from server to client
Authors: Michiaki Tatsubori, Toyotaro Suzumura
Venue: WWW
Year: 2009

Web applications often use HTML templates to separate the webpage presentation from its underlying business logic and objects. This is now the de facto standard programming model for Web application development. This paper proposes a novel implementation for existing server-side template engines, FlyingTemplate, for (a) reduced bandwidth consumption in Web application servers, and (b) off-loading HTML generation tasks to Web clients. Instead of producing a fully-generated HTML page, the proposed template engine produces a skeletal script which includes only the dynamic values of the template parameters and the bootstrap code that runs on a Web browser at the client side. It retrieves a client-side template engine and the payload templates separately. With the goals of efficiency, implementation transparency, security, and standards compliance in mind, we developed FlyingTemplate with two design principles: effective browser cache usage, and reasonable compromises which restrict the template usage patterns and relax the security policies slightly but in a controllable way. This approach allows typical template-based Web applications to run effectively with FlyingTemplate. As an experiment, we tested the SPECweb2005 banking application using FlyingTemplate without any other modifications and saw throughput improvements from 1.6x to 2.0x in its best mode. In addition, FlyingTemplate can enforce compliance with a simple security policy, thus addressing the security problems of client-server partitioning in the Web environment.
Web content accessibility guidelines: from 1.0 to 2.0
Authors: Miquel Termens, Mireia Ribera, Mercè Porras, Marc Boldú, Andreu Sulé, Pilar Paris
Venue: WWW
Year: 2009

This poster explains the changes introduced in the Web Content Accessibility Guidelines (WCAG) 2.0 from WCAG 1.0 and proposes a checklist for adapting existing websites. Finally, it describes the most common criticisms of the WCAG and places them in the context of its origin and initial aims.
Automatically filling form-based web interfaces with free text inputs
Authors: Guilherme A. Toda, Eli Cortez, Filipe de Sá Mesquita, Altigran Soares da Silva, Edleno Silva de Moura, Marden S. Neubert
Venue: WWW
Year: 2009

On the web of today the most prevalent solution for users to interact with data-intensive applications is the use of form-based interfaces composed by several data input fields, such as text boxes, radio buttons, pull-down lists, check boxes, etc. Although these interfaces are popular and effective, in many cases, free text interfaces are preferred over form-based ones. In this paper we discuss the proposal and the implementation of a novel IR-based method for using data rich free text to interact with form-based interfaces. Our solution takes a free text as input, extracts implicitly data values from it and fills appropriate fields using them. For this task, we rely on values of previous submissions for each field, which are freely obtained from the usage of form-based interfaces
Ranking community answers via analogical reasoning
Authors: Xudong Tu, Xin-Jing Wang, Dan Feng, Lei Zhang
Venue: WWW
Year: 2009

Due to the lexical gap between questions and answers, automatically detecting right answers becomes very challenging for community question-answering sites. In this paper, we propose an analogical reasoning-based method. It treats questions and answers as relational data and ranks an answer by measuring the analogy of its link to a query with the links embedded in previous relevant knowledge; the answer that links in the most analogous way to the new question is assumed to be the best answer. We based our experiments on 29.8 million Yahoo!Answer question-answer threads and showed the effectiveness of the approach.
News article extraction with template-independent wrapper
Authors: Junfeng Wang, Xiaofei He, Can Wang, Jian Pei, Jiajun Bu, Chun Chen, Ziyu Guan, Gang Lu
Venue: WWW
Year: 2009

We consider the problem of template-independent news extraction. The state-of-the-art news extraction method is based on template-level wrapper induction, which has two serious limitations. 1) It cannot correctly extract pages belonging to an unseen template until the wrapper for that template has been generated. 2) It is costly to maintain up-to-date wrappers for hundreds of websites, because any change of a template may lead to the invalidation of the corresponding wrapper. In this paper we formalize news extraction as a machine learning problem and learn a template-independent wrapper using a very small number of labeled news pages from a single site. Novel features dedicated to news titles and bodies are developed respectively. Correlations between the news title and the news body are exploited. Our template-independent wrapper can extract news pages from different sites regardless of templates. In experiments, a wrapper is learned from 40 pages from a single news site. It achieved 98.1% accuracy over 3,973 news pages from 12 news sites.
Competitive analysis from click-through log
Authors: Gang Wang, Jian Hu, Yunzhang Zhu, Hua Li, Zheng Chen
Venue: WWW
Year: 2009

Existing keyword suggestion tools from various search engine companies could automatically suggest keywords related to the advertisers' products or services, counting in simple statistics of the keywords, such as search volume, cost per click (CPC), etc. However, the nature of the generalized Second Price Auction suggests that better understanding the competitors' keyword selection and bidding strategies better helps to win the auction, other than only relying on general search statistics. In this paper, we propose a novel keyword suggestion strategy, called Competitive Analysis, to explore the keyword based competition relationships among advertisers and eventually help advertisers to build campaigns with better performance. The experimental results demonstrate that the proposed Competitive Analysis can both help advertisers to promote their product selling and generate more revenue to the search engine companies.
Dataplorer: a scalable search engine for the data web
Authors: Haofen Wang, Qiaoling Liu, Gui-Rong Xue, Yong Yu, Lei Zhang, Yue Pan
Venue: WWW
Year: 2009

More and more structured information in the form of semantic data is nowadays available. It offers a wide range of new possibilities especially for semantic search and Web data integration. However, their effective exploitation still brings about a number of challenges, e.g. usability, scalability and uncertainty. In this paper, we present Dataplorer, a solution designed to address these challenges. We consider the usability through the use of hybrid queries and faceted search, while still preserving the scalability thanks to an extension of inverted index to support this type of query. Moreover, Dataplorer deals with uncertainty by means of a powerful ranking scheme to find relevant results. Our experimental results show that our proposed approach is promising and it makes us believe that it is possible to extend the current IR infrastructure to query and search the Web of data.