User-schedule-based Web page recommendation

Tetsuya Oishi, Shunsuke Kuramoto, Hiroto Nagata, Tsunenori Mine, Ryuzo Hasegawa, Hiroshi Fujita, Miyuki Koshimura

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

3 Citations (Scopus)

Abstract

In web retrieval, it is often the case that the results given by search engines are not just what we want. To solve this problem there have been many studies on improving queries to be submitted to search engines. However, they are still insufficient due to lack of consideration on time information. To remedy this we propose a user-schedule-based web page recommendation method. The method makes use of a user's schedule to make the recommendation suite to his/her requests. In addition, an algorithm for extracting related words is introduced as a key technique in this method. Some preliminary experiments show very promising results in recommending web pages relevant to users requests. We also confirmed that this algorithm outper-forms a method using mutual information.

Original languageEnglish
Title of host publicationProceedings of the IEEE/WIC/ACM International Conference on Web Intelligence, WI 2007
Pages776-779
Number of pages4
DOIs
Publication statusPublished - Dec 1 2007
EventIEEE/WIC/ACM International Conference on Web Intelligence, WI 2007 - Silicon Valley, CA, United States
Duration: Nov 2 2007Nov 5 2007

Publication series

NameProceedings of the IEEE/WIC/ACM International Conference on Web Intelligence, WI 2007

Other

OtherIEEE/WIC/ACM International Conference on Web Intelligence, WI 2007
CountryUnited States
CitySilicon Valley, CA
Period11/2/0711/5/07

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All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications

Cite this

Oishi, T., Kuramoto, S., Nagata, H., Mine, T., Hasegawa, R., Fujita, H., & Koshimura, M. (2007). User-schedule-based Web page recommendation. In Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence, WI 2007 (pp. 776-779). [4427188] (Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence, WI 2007). https://doi.org/10.1109/WI.2007.4427188