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Content hole search in community-type content using Wikipedia

Published: 14 December 2009 Publication History

Abstract

SNSs and blogs, both of which are maintained by a community of people, have become popular in Web 2.0. We call these content as "Community-type content." This community is associated with the content, and those who use or contribute to community-type content are considered as members of the community. Occasionally, the members of a community do not understand the theme of the content from multiple viewpoints, hence, the amount of information is often insufficient. It is convenient to present the user missed information. In this way, when Web 2.0 became popular, the content on the Internet and type of users are changed. We believe that there is a need for next-generation search engines in Web 2.0. We require a search engine that can search for information users are unaware of; we call such information as "content holes." In this paper, we propose a method for searching content holes in community-type content. We attempt to extract and represent content holes from discussions on SNSs and blogs. Conventional Web search technique is generally based on similarities. On the other hand, our content-hole search is a different search. In this paper, we classify and represent a number of images for different searching methods; we define content holes and as the first step toward realizing our aim, we propose a content-hole search system using Wikipedia.

References

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Kentaro Torisawa, Stijn De Saeger, Yasunori Kakizawa, Jun'ichi Kazama, Masaki Murata, Daisuke Noguchi, Asuka Sumida, "TORISHIKI-KAI, An Autogenerated Web Search Directory", Universal Communication, International Symposium, pp. 179--186, 2008
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Seung-Jin Lim and Yiu-Kai Ng, "An Automated Change-detection Algorithm for HYML documents Based on Semantic Hierarchies," Proc. the 17th Intl. Conf. on Data Engineering (ICDE'01), pp. 303--312, Heidelberg, Germany, April 2001.
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Nakayama, K., Pei, M., Erdmann, M., Ito, M., Shirakawa, M., Hara, T. and Nishio, S., "Wikipedia Mining - Wikipedia as a Corpus for Knowledge Extraction", in Proceedings of Annual Wikipedia Conference (Wikimania), 2008
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Evgeniy Gabrilovich, Shaul Markovitch: Computing Semantic Relatedness Using Wikipedia-based Explicit Semantic Analysis, Proceedings of the International Joint Conference on Artificial Intelligence 2007 (IJCAI 2007), pp. 1606--1611, Hyderabad, India, January 2007.
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  • (2012)How the web can help WikipediaProceedings of the 6th International Conference on Ubiquitous Information Management and Communication10.1145/2184751.2184763(1-10)Online publication date: 20-Feb-2012

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    iiWAS '09: Proceedings of the 11th International Conference on Information Integration and Web-based Applications & Services
    December 2009
    763 pages
    ISBN:9781605586601
    DOI:10.1145/1806338
    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: 14 December 2009

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    Author Tags

    1. SNS
    2. blog
    3. community
    4. content hole search

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    • Grant-in-Aid, Information Explosion Project

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    • (2012)How the web can help WikipediaProceedings of the 6th International Conference on Ubiquitous Information Management and Communication10.1145/2184751.2184763(1-10)Online publication date: 20-Feb-2012

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