Personalization by Relevance Ranking Feedback in Impression-based Retrieval for Multimedia Database
نویسندگان
چکیده
This paper proposes an approach to personalization by relevance `ranking’ feedback in impression-based retrieval for a multimedia database. Impression-based retrieval is a kind of ambiguous retrieval, and it enables a database user to find not only a known data but also an unknown data to him/her. Conventional approaches using relevance feedback technique only return a binary information: `relevant’ or `not relevant’, for his/her retrieval intention. In this paper, he/she returns each relevance ranking to his/her retrieval intention for top n data of a retrieval result. From this feedback information, an adjustment data inherent to him/her is produced, and utilized for personalization. We show its effectiveness by an evaluation using our pilot system.
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تاریخ انتشار 2013