The dissertation deeply analyzes its sparsity problem which depresses recommendation quality and recommending integrality problem which influences consumers’satisfaction, introduces“concept hierarchy”and“community filtering”techniques to improve collaborative filtering algorithm, and designes improved algorithms to realize the strategies proposed above.
对该算法中影响推荐质量的稀疏性问题和影响用户满意度的推荐完整性问题进行了深入分析,引入了“概念分层”和“社区过滤”技术对协同过滤算法进行改进,设计出了能够实现论文所提出的推荐策略的改进算法。
参考来源 - 电子商务个性化推荐系统中协同过滤技术及应用研究·2,447,543篇论文数据,部分数据来源于NoteExpress
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