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Journal of Computers EIMEDLINEScopus

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篇名 A Hybrid Recommendation Method Based on Feature for Offline Book Personalization
卷期 30:5
作者 Xixi Li 、 Jiahao Xing 、 Haihui Wang 、 Lingfang Zheng 、 Suling Jia 、 Qiang Wang
頁次 001-017
關鍵字 collaborative filtering 、 customer preference 、 hybrid recommendation 、 offline book transaction 、 EI 、 MEDLINE 、 Scopus
出刊日期 201910
DOI 10.3966/199115992019103005001

中文摘要

英文摘要

Recommendation system has been widely used in different areas. Collaborative filtering focuses on rating, ignoring the features of items itself. In order to effectively evaluate customers’ preferences on books, taking into consideration of the characteristics of offline book retail, we use LDA model to calculate customers’ preference on book topics and use word2vec to calculate customers’ preference on book types. When forecasting rating on books, we take two factors into consideration: similarity of customers and correlation between customers and books. Experiment shows that our hybrid recommendation method based on features performances better than single recommendation method in offline book retail data.

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