基于语义的兴趣偏好分析模型研究

Research on Interest Preference Analysis Model Based on Semantics

个性图书推荐是根据读者的历史借阅行为,运用现代计算机挖掘技术,寻找读者与图书之间的强关联部分。通过分析读者在OPAC图书馆管理系统中留下的痕迹,计算痕迹语义的相似度,构建痕迹网络,建立读者与图书之间的痕迹语义偏好分析模型。旨在为图书馆"千人千面"的图书推荐策略提供建议,以提升图书推荐质量,助力校园文化建设。

Personal book recommendation is based on readers'historical borrowing behavior,using modern computer mining technology to find the strong correlation between readers and books.By analyzing the traces left by readers in OPAC library management system,the similarity of traces semantics is calculated,traces network is constructed,and the model of traces semantics preference analysis between readers and books is established.The purpose is to provide suggestions for the library's book recommendation strategy of"thousands of people and thousands of faces",in order to improve the quality of book recommendation and help the construction of campus culture.