Evaluating reranking methods using wikipedia features

Koji Kurakado, Tetsuya Oishi, Ryuzo Hasegawa, Hiroshi Fujita, Miyuki Koshimura

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Many people these days access a vast document on the Web very often with the help of search engines such as Google. However, even if we use the search engine, it is often the case that we cannot find desired information easily. In this paper, we extract related words for the search query by analyzing link information and category structure. we aim to assist the user in retrieving web pages by reranking search results.

Original languageEnglish
Title of host publicationICAART 2011 - Proceedings of the 3rd International Conference on Agents and Artificial Intelligence
Pages376-381
Number of pages6
Publication statusPublished - Jul 14 2011
Event3rd International Conference on Agents and Artificial Intelligence, ICAART 2011 - Rome, Italy
Duration: Jan 28 2011Jan 30 2011

Publication series

NameICAART 2011 - Proceedings of the 3rd International Conference on Agents and Artificial Intelligence
Volume1

Other

Other3rd International Conference on Agents and Artificial Intelligence, ICAART 2011
CountryItaly
CityRome
Period1/28/111/30/11

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All Science Journal Classification (ASJC) codes

  • Artificial Intelligence

Cite this

Kurakado, K., Oishi, T., Hasegawa, R., Fujita, H., & Koshimura, M. (2011). Evaluating reranking methods using wikipedia features. In ICAART 2011 - Proceedings of the 3rd International Conference on Agents and Artificial Intelligence (pp. 376-381). (ICAART 2011 - Proceedings of the 3rd International Conference on Agents and Artificial Intelligence; Vol. 1).