一种改进的Slope One协同过滤算法  

Improved Slope One Algorithm for Collaborative Filtering

作　　者：王毅[1] 楼恒越[2] 

机构地区：[1]西南交通大学信息科学与技术学院,成都610036 [2]四川师范大学计算机科学学院,成都610101

出　　处：《计算机科学》2011年第B10期192-194,共3页Computer Science

摘　　要：相对传统的基于用户项目评分的协同过滤算法,Slope One算法简单、高效。但该算法依赖于大量用户对待预测项目的评分,如果对预测项目评分的用户较少,没有考虑用户本身的喜好,将对评分预测的结果有影响。因此,引入描述关键字的语义相似度,利用关键字相似性度量项目间的相似程度,并结合该用户对其他项目的评分,提出一种基于项目语义相似度的改进Slope One算法,并在标准的MovieLens数据集上进行预测实验。实验数据表明,相对于原算法,改进的算法在一定程度上提高了预测的准确性。Compared to traditional rating-based collaborative filtering algorithm,the Slope One algorithm is simple and efficient.However,the Slope One algorithm relies on a large number of users＇ ratings to the item which should be predicted.The rating prediction is affected when users＇ ratings are not enough and it does not consider the users＇ habits.For the reason,the semantic similarity of the keyword to describe the items was introduced,which measures the degree of similarity between item-pairs,then a combination of items＇ semantic similarity and the Slope One algorithm was proposed.Finally,by the standard data set MovieLens,the data of the experiment＇s result show that the improved algorithm improvers the accuracy of the original algorithm.

关 键 词：协同过滤 SLOPE One算法 用户推荐 语义相似 

分 类 号：TP274.2[自动化与计算机技术—检测技术与自动化装置]