计算机技术与发展Issue(1)：35-38,4.DOI:10.3969/j.issn.1673-629X.2014.01.009
基于遗传算法的聚类与协同过滤组合推荐算法
Recommendation Algorithm of Combining Clustering with Collaborative Filtering Based on Genetic Algorithm
摘要
Abstract
When dealing with item recommendation with large data sets,there are problems of efficiency and the low quality of the results for collaborative filtering. K-means clustering has a better performance when processing large data sets. In order to solve problems of col-laborative filtering,genetic algorithm can be used to combine clustering and collaborative filtering for item recommendation to improve the efficiency and quality of the recommendation algorithm,reduce the complexity of item recommendation by the combination of cluste-ring and collaborative filtering. Do comparative experiments using the combination algorithm in Movielens data sets. The experimental re-sults show that,compared with pure collaborative filtering recommendation,using genetic algorithm to combine clustering with collabora-tive filtering for item recommendation can get a better quality results.关键词
遗传算法/k均值聚类/item-based协同过滤/项目推荐Key words
genetic algorithm/k-means clustering/item-based collaborative filtering/item recommendation分类
信息技术与安全科学引用本文复制引用
冯智明,苏一丹,覃华,邓海..基于遗传算法的聚类与协同过滤组合推荐算法[J].计算机技术与发展,2014,(1):35-38,4.基金项目
教育部人文社会科学研究项目(11YJAZH080) （11YJAZH080）
