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| Group Recommendation Based on Attribute Mining of Book Reviews |
Xiong Huixiang1( ),Li Xiaomin1,Li Yueyan2 |
1School of Information Management, Central China Normal University, Wuhan 430079, China
2School of Information Management, Nanjing University, Nanjing 210023, China |
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Abstract [Objective] This paper conducts group recommendation using the relationship among users, tags and books.[Methods] First, we used the K-means algorithm to cluster users and books. Then, we calculated cosine similarity of the two groups. Third, we compared various books based on their reviews. Finally, we sorted and clustered books to personalize the recommendation results.[Results] We examined the proposed model with data from “Douban Net” and our model recommended better resources for user groups.[Limitations] The sample data size needs to be expanded.[Conclusions] The proposed model improves the personalized recommendation of books.
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Received: 11 June 2019
Published: 26 April 2020
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Corresponding Authors:
Huixiang Xiong
E-mail: hxxiong@mail.ccnu.edu.cn
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