Employing neighborhood reduction for alleviating sparsity and cold start problems in user-based collaborative filtering

IF 1.7 3区计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS

Information Retrieval Journal Pub Date : 2020-06-19 DOI:10.1007/s10791-020-09378-w

Zhipeng Zhang, Yao Zhang, Yonggong Ren

引用次数: 17

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利用邻域约简缓解用户协同过滤中的稀疏性和冷启动问题

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Information Retrieval Journal 工程技术-计算机：信息系统

CiteScore

6.20

自引率

0.00%

发文量

审稿时长

13.5 months

期刊介绍： The journal provides an international forum for the publication of theory, algorithms, analysis and experiments across the broad area of information retrieval. Topics of interest include search, indexing, analysis, and evaluation for applications such as the web, social and streaming media, recommender systems, and text archives. This includes research on human factors in search, bridging artificial intelligence and information retrieval, and domain-specific search applications.