社交网络的分布式协同过滤算法在煤炭产业的应用

随着电子商务的高速发展,推荐系统成为煤炭产业网站的核心技术之一。协同过滤算法是推荐系统中的主要方法。由于社交网络的发展,用户之间往往通过推荐喜欢的商品给熟悉用户,这种基于社交网络的协同过滤算法往往能够更加准确的完成网站的推荐工作。但是,随着煤炭销售数据规模的增大,传统的基于社交网络的协同过滤算法不能有效地完成推荐工作。针对煤炭数据规模大、分析复杂问题,提出了基于云平台的分布式社交网络协同过滤算法,该算法分布式完成系统推荐工作,具有很高的效率。

Application of Distributed Collaborative Filtering Algorithm of Social Network in Coal Industry

With the development of E-commerce, recommender system is becoming one of the core technologies in coal industry websites. Collaborative filtering algorithm is the main method in recommender system. Because of the developing of social networks, the users usually recommend their favorite items to their familiar users, and this kind of social network based collaborative filtering algorithm could complete the recommendation works much more precisely. However, with the increasing of scale of coal sales, traditional social network based collaborative filtering algorithm could not complete the recommendation work effectively. Focusing on the large scale coal data and the complex problem of analyzing them, we propose distributed social network based collaborative filtering algorithm on cloud platform, and this algorithm could complete the recommendation work distributed, and has high efficiency.