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Refining preference-based search results through Bayesian filtering

Zhang, Jiyong ; Pu, Pearl

Proceedings of the 12th international conference on intelligent user interfaces, 28 January 2007, pp.294-297

ISBN: 1595934812 ; ISBN: 9781595934819 ; DOI: 10.1145/1216295.1216350

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  • Nhan đề:
    Refining preference-based search results through Bayesian filtering
  • Tác giả: Zhang, Jiyong ; Pu, Pearl
  • Chủ đề: Bayesian Filtering ; Interaction Effort ; Preference-Based Search ; Computer Science
  • Là 1 phần của: Proceedings of the 12th international conference on intelligent user interfaces, 28 January 2007, pp.294-297
  • Mô tả: Preference-based search (PBS) is a popular approach for helping consumers find their desired items from online catalogs. Currently most PBS tools generate search results by a certain set of criteria based on preferences elicited from the current user during the interaction session. Due to the incompleteness and uncertainty of the user's preferences, the search results are often inaccurate and may contain items that the user has no desire to select. In this paper we develop an efficient Bayesian filter based on a group of users' past choice behavior and use it to refine the search results by filtering out items which are unlikely to be selected by the user. Our preliminary experiment shows that our approach is highly promising in generating more accurate search results and saving user's interaction effort.
  • Ngôn ngữ: English
  • Số nhận dạng: ISBN: 1595934812 ; ISBN: 9781595934819 ; DOI: 10.1145/1216295.1216350

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