| 吴彦文,牛晓璇,胡炎贵,王馨悦,何秀玲.数字图书资源聚合及精准化推荐方法研究[J].数字图书馆论坛,2018,(11):11~18 |
| 数字图书资源聚合及精准化推荐方法研究 |
| Research on Precision Recommendation Algorithm for Digital Resource with Integration Method |
| 投稿时间：2018-11-03 |
| DOI：10.3772/j.issn.1673-2286.2018.11.002 |
| 中文关键词: 数字资源聚合;作者耦合;语义网;协同过滤 |
| 英文关键词: Integration of Digital Resource; Author Coupling; Semantic Network; Collaborative Filtering |
| 基金项目:本研究得到教育部人文社会科学研究规划基金项目"智慧教室环境下课堂交互有效性量化研究"(编号:17YJA880030)资助. |
| 作者 | 单位 | | 吴彦文 | 华中师范大学 | | 牛晓璇 | 华中师范大学 | | 胡炎贵 | 华中师范大学 | | 王馨悦 | 华中师范大学 | | 何秀玲 | 华中师范大学 |
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| 中文摘要: |
| 针对数字资源信息过载、信息异构、资源推荐效果不理想等问题,改进传统数字资源聚合模型和相似度计算方式,本文提出一种数字资源聚合模型,并融合协同过滤的推荐思想,利用该聚合模型进行相似度计算得出资源和用户的近邻集合,基于此设计精准化资源推荐算法,最后以馆藏图书资源为例对模型进行验证.结果表明,本文构建的方法能够对数字资源进行有效聚合,并挖掘图书的语义信息,同时结合用户兴趣模型,为用户提供精准化的资源推荐. |
| 英文摘要: |
| In view of the problems of information overload, heterogeneous information and unsatisfactory recommendation effect of digital resources, this paper aims to improve the traditional digital resource integration model and similarity calculation method, and combine a multi-label collaborative filtering methods to improve the accuracy of recommendation. Based on the idea of collaborative filtering recommendation, a digital resource integration method is used to calculate the similarity then find close neighbors of resources and users. Based on this, the precision of resource recommendation algorithm is constructed. Finally, the collection of library resources is taken as an example to verify the model’s effectiveness. The results show that the method can effectively aggregate the digital resources, excavate the semantic information of books, and combine the user interest model to provide the users with accurate resource recommendations. |
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