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Title:
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PREFERENCE CLARIFICATION RECOMMENDER SYSTEM BY SEARCHING ITEMS BEYOND CATEGORY |
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Author(s):
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Keiki Takadama, Fumiaki Sato, Masayuki Otani, Kiyohiko Hattori, Hiroyuki Sato, Tomohiro Yamaguchi |
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ISBN:
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978-972-8939-75-5 |
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Editors:
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Katherine Blashki |
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Year:
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2012 |
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Edition:
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Single |
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Keywords:
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Recommender system, web shopping, decision support, preference clarification, category. |
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Type:
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Full Paper |
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First Page:
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3 |
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Last Page:
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10 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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The paper proposes a novel recommender system which supports users (buyers) to clarify the most appropriate preference by recommending other categories items that almost meet the attributes selected by users. Such an advantage is achieved by both (i) the preference concretization of users which is difficult for the content-based recommender systems and (ii) the preference change of users which is difficult for the collaborative recommender systems. To investigate the effectiveness of the proposed system, we conducted the human-subject experiments and found that the proposed system supports users to find their desirable items by clarifying their preference. In detail, the following implications have been revealed: (1) users clarify their preference by comparing items which are classified in different categories; (2) the item recommendation based on the selected attribute similarity contributes to clarifying the users preference through a change of their preference; and (3) the item recommendation based on the function similarity contributes to clarifying the users preference through a concretization of their preference. |
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