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Implementation of Recommender System Based on Personalized Search Using Intimacy in SNS

机译:基于个性化搜索的亲密关系推荐系统在SNS中的实现

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Recently, a search system has been a trend of personalization such as recommendation systems and social searches. Because, each users receive different results for the same queries by using user preference and interesting. Specially, a social relation is a most important factor of search system, and therefore, many recommender system using have been proposed. However, existing recommender systems typically return a set of search results based on a user's query without considering user interests and preference. Therefore, the identical query from each user will generate the same set of results displayed in the same way for all users. To overcome this restriction, this paper proposes a recommender system based on personalized search using intimacy in SNS and describe a prototype of our recommender system.
机译:最近,搜索系统已经成为个性化的趋势,例如推荐系统和社交搜索。因为,每个用户通过使用用户喜好和兴趣获得相同查询的不同结果。特别地,社会关系是搜索系统的最重要因素,因此,已经提出了许多使用推荐系统的建议。但是,现有的推荐系统通常基于用户的查询返回一组搜索结果,而不考虑用户的兴趣和偏好。因此,来自每个用户的相同查询将为所有用户生成以相同方式显示的相同结果集。为了克服这种限制,本文提出了一种基于个性化搜索的推荐系统,该系统使用SNS中的亲密关系进行个性化搜索,并描述了我们的推荐系统的原型。

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