• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>CIRP Conference on Industrial Product-Service Systems >College Library Personalized Recommendation System Based on Hybrid Recommendation Algorithm
【24h】

College Library Personalized Recommendation System Based on Hybrid Recommendation Algorithm

机译：基于混合推荐算法的大学图书馆个性化推荐系统

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

When the number of books provided by library is relatively large, it becomes difficult for user to select appropriate book from a lot of candidate books. In this case, this paper designs a personalized recommendation system for college libraries based on hybrid recommendation algorithm. First of all, paper studies the application of collaborative filtering and content-based recommendation algorithm in the recommendation of university books, which involves reader classification, the establishment of user-item scoring matrix, the construction of vector space model and the calculation of similarity among users. And considering the characteristics of books and readers in universities, the user - item scoring matrix is improved, and clustering is used to alleviate the data sparsity problem. Do comparative experiments using the hybrid algorithm in data sets of Library of Inner Mongolia University of Technology. The results demonstrate that the hybrid methods can provide more accurate recommendations than pure approaches. Finally, the Spark big data platform combined with the hybrid recommendation algorithm is used to achieve the personalized book recommendation system design.
机译：当库提供的书籍数量相对较大时，用户难以从许多候选书中选择合适的书。在这种情况下，本文为基于混合推荐算法的大学图书馆设计了个性化推荐系统。首先，论文研究了协同过滤和基于内容的推荐算法在大学书籍推荐中的应用，涉及读者分类，建立用户 - 项目评分矩阵，矢量空间模型的构建和相似性的计算用户。并考虑大学书籍和读者的特征，提高了用户 - 项目评分矩阵，并且使用聚类来缓解数据稀疏问题。使用内蒙古工业大学图书馆数据集的混合算法进行比较实验。结果表明，混合方法可以提供比纯方法更准确的建议。最后，Spark大数据平台与混合推荐算法相结合，用于实现个性化的书籍推荐系统设计。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号