Web日志在协同过滤推荐算法中的应用  

Application of Web Log in Collaborative Filtering Recommendation Algorithm

作　　者：张校慧[1] 谢倩[2] 

机构地区：[1]黄河水利职业技术学院信息工程系,开封475004 [2]开封大学软件学院,开封475004

出　　处：《现代计算机》2011年第4期68-71,共4页Modern Computer

摘　　要：协同过滤算法近年来在电子商务推荐系统中得到了广泛的应用,但该算法也存在数据稀疏性和缺乏个性化等问题,这些问题影响了推荐算法的效率和准确性。主要针对以上问题,提出引入Web日志分析的协同过滤算法,将用户对商品的隐性兴趣转化为显性兴趣,同时利用用户聚类等相关技术,不仅解决数据稀疏的问题也提高推荐的准确性。Collaborative filtering algorithm has been widely used in the electronic commerce recommendation system in recent years,but collaborative filtering algorithm also has some problems,such as data sparseness and lack of individuation,these problems affected the efficiency and accuracy of recommendation algorithm.According to the problems,proposes the method of Web log analysis and user clustering related technology,this method transforms implicit interest to explicit interest of user for commodities,it not only solves the problem sparse data but also improve the recommend of accuracy.

关 键 词：日志分析 用户聚类 协同过滤 电子商务 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]