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This paper proposes a personal-value based item modeling, which is used for explaining recommendation. In recent years, studies on improvements of user's satisfactions for recommender systems by showing process of recommendation have been popular in addition to precision of recommendation. The proposed method extracts personal values of reviewers of a movie as the influence of movie's attribute on...
This paper presents consideration about applicability of recommender system based on personal-value-based user model. Existing methods such as collaborative and content-based approaches tend to be less-accurate for new users and items owing to the lack of the relation between items and users' preference. While existing recommender systems usually employ user preference of items to make recommendations,...
This paper proposes user and item modeling methods towards recommender systems based on personal values. Marketing fields have been taking notice of personal values, because that such values are significantly related to user preference. While existing recommender systems usually employ user preference of items to make recommendations, proposed method focuses on users' personal values, which mean value...
This paper proposes an evaluation method for informative reviews depending on personal values, and shows results of analyzing actual online reviews. Reviews of items are posted by users on many shopping sites. A user who is considering purchasing an item will refer to reviews about it. However, it becomes overloads if there are so many reviews for the item. In particular, there exist reviewers who...
This paper proposes a user modeling method and a recommender system based on personal values. Existing recommender systems usually employ user preference of items to make recommendations. On the other hand, marketing fields have been taking notice of personal values because of its significant relation to potential preferences of users. Although personal values are expected to bring a new framework...
A method for mining association rules that reflect the behaviors of past users is proposed for an adaptive search engine. The logs of the users' retrieving behaviors are described with the resource description framework model, from which association rules that reflect successful retrieving behaviors are extracted. The extracted rules are used to improve the performance of a metadata-based search engine...
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