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User Preferences to Attributes of Books for Personalized Recommendation

机译:用户对书籍属性进行个性化推荐的首选项

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摘要

Personalized recommendation and user preference to books have aroused lots of attention both domestically and abroad and fruitful achievements have been made in this area. Nevertheless, the previous preference models mainly focus on the content of books and ignore the attribute of price of a book. In an actual book recommendation system, the price influences the consumers' buying behavior to a large extent and should be considered seriously. Based on the existing preference models, in addition to the attributes of the publisher, publishing date, discount, and the other consumers' reviews, this study takes the attribute of price into consideration to a particular book. The dummy variable regression method is employed to analyze the data mainly from Amazon. Through data analysis and investigation, this paper tries to explore the importance of its different attributes in the user preference to a book. In accordance with the data analysis, some suggestions are provided for book recommendation system design and relevant website modification.
机译:个性化推荐和用户对书籍的偏爱引起了国内外的广泛关注,并在这一领域取得了丰硕的成果。但是,先前的偏好模型主要关注书籍的内容,而忽略了书籍价格的属性。在实际的图书推荐系统中,价格在很大程度上影响着消费者的购买行为,应该认真考虑。基于现有的偏好模型,除了出版商,出版日期,折扣和其他消费者评论的属性外,本研究还考虑了特定书籍的价格属性。虚拟变量回归方法主要用于分析来自Amazon的数据。通过数据分析和调查,本文试图探索其不同属性在用户对书籍的偏爱中的重要性。根据数据分析,为图书推荐系统的设计和相关网站的修改提供了一些建议。

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