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Answering relationship queries on the web

Published: 08 May 2007 Publication History

Abstract

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.

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    cover image ACM Conferences
    WWW '07: Proceedings of the 16th international conference on World Wide Web
    May 2007
    1382 pages
    ISBN:9781595936547
    DOI:10.1145/1242572
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Publication History

    Published: 08 May 2007

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    Author Tags

    1. relationship query
    2. web search

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    WWW'07
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    WWW'07: 16th International World Wide Web Conference
    May 8 - 12, 2007
    Alberta, Banff, Canada

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    Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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    Cited By

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    • (2017)An Empirical Evaluation of Techniques for Ranking Semantic AssociationsIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2017.273597029:11(2388-2401)Online publication date: 1-Nov-2017
    • (2017)Building spatial temporal relation graph of concepts pair using web repositoryInformation Systems Frontiers10.1007/s10796-016-9676-419:5(1029-1038)Online publication date: 1-Oct-2017
    • (2016)Efficient Algorithms for Association Finding and Frequent Association Pattern MiningThe Semantic Web – ISWC 201610.1007/978-3-319-46523-4_8(119-134)Online publication date: 23-Sep-2016
    • (2015)Temporal Learning of Semantic Relations between Concepts Using Web RepositoryProceedings of the 2015 11th International Conference on Semantics, Knowledge and Grids (SKG)10.1109/SKG.2015.18(239-243)Online publication date: 19-Aug-2015
    • (2015)Improving Cross-Document Knowledge Discovery Through Content and Link Analysis of Wikipedia KnowledgeTransactions on Large-Scale Data- and Knowledge-Centered Systems XXI10.1007/978-3-662-47804-2_8(161-184)Online publication date: 17-Jul-2015
    • (2014)Product weakness finder: an opinion-aware system through sentiment analysisIndustrial Management & Data Systems10.1108/IMDS-05-2014-0159114:8(1301-1320)Online publication date: 2-Sep-2014
    • (2014)Mining temporal explicit and implicit semantic relations between entities using web search enginesFuture Generation Computer Systems10.1016/j.future.2013.09.02737(468-477)Online publication date: Jul-2014
    • (2014)Explass: Exploring Associations between Entities via Top-K Ontological Patterns and FacetsThe Semantic Web – ISWC 201410.1007/978-3-319-11915-1_27(422-437)Online publication date: 19-Oct-2014
    • (2013)A Novel Method for Mining the Advisor-Student Relationships in Academic Social NetworkAdvanced Materials Research10.4028/www.scientific.net/AMR.655-657.1795655-657(1795-1799)Online publication date: Jan-2013
    • (2013)Chinese Comparative Sentence Identification Based on the Combination of Rules and StatisticsPart II of the Proceedings of the 9th International Conference on Advanced Data Mining and Applications - Volume 834710.1007/978-3-642-53917-6_27(300-310)Online publication date: 14-Dec-2013
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