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Applications of concept relation network to web search

Published: 25 March 2011 Publication History

Abstract

In this paper, we propose a method to extract concepts from the search results of a query. By treating each retrieved concept as a query, it recursively constructs a network of concepts, called Concept Relation Network (CRN), representing different semantic interpretations of the queries. CRN is a semantic network that can be automatically constructed and maintained using existing search engines (e.g., Google) on the web. By employing large scale commercial search engines, CRN can derive a large number of highly coherent, highly related concepts. The semantic information stored in CRN can be used to improve the performance of web search systems, such that more accurate information can be recommended to the user. In this paper, we propose several applications of CRN to web search.

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K. W.-T. Leung, D. L. Lee, and W.-C. Lee. Personalized web search with location preferences. In Proc. of the ICDE Conference, 2010.
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K. W.-T. Leung, W. Ng, and D. L. Lee. Personalized concept-based clustering of search engine queries. IEEE TKDE, 2008.
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H. Liu and P. Singh. Focusing on conceptnet's natural language knowledge representation. In Proc. of the KES Conference, 2004.
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F. Suchanek, G. Kasneci, and G. Weikum. YAGO: A core of semantic knowledge - unifying WordNet and Wikipedia. In Proc. of the WWW Conference, 2007.

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LWDM '11: Proceedings of the 1st International Workshop on Linked Web Data Management
March 2011
41 pages
ISBN:9781450306089
DOI:10.1145/1966901

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 25 March 2011

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Author Tags

  1. concept
  2. ontology
  3. query clustering
  4. search engines
  5. semantic network
  6. web search

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