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网络的普及和社会化媒体的兴起为图书推荐提供了崭新的发展平台。如何改进推荐算法,使图书推荐结果更符合读者的需求,已成为相关读书网站及各领域学者关注和研究的重点。文章通过构建图书基因组来描述图书各个方面的特征,分析用户对图书基因的偏好;根据用户标注信息建立用户兴趣集,构建用户“相邻”关系;最后,提出基于图书基因组的个性化图书推荐算法。通过实验证实,该算法能有效提高推荐结果的准确度。
The popularization of the Internet and the rise of social media have provided a brand new platform for the development of book recommendation. How to improve the recommendation algorithm and make the book recommendation result more in line with the needs of the readers has become the focus of attention and research of the relevant study websites and scholars in various fields. This paper constructs the book genome to describe the characteristics of every aspect of the book, analyzes the user’s preference of the book gene, builds the user interest set according to the user’s annotation information, constructs the user “neighborhood ” relationship; finally, proposes the personalized book based on the book genome Recommended algorithm. Experiments show that the algorithm can effectively improve the accuracy of the recommended results.