###
DOI:
Journal of Software:2007.18(10):2403-2411

基于云模型的协同过滤推荐算法
张光卫,李德毅,李鹏,康建初,陈桂生
(北京航空航天大学,软件开发环境国家重点实验室,北京,100083;山东建筑大学,计算机科学与技术学院,山东,济南,250101;中国电子工程系统研究所,北京,100840;哈尔滨工业大学,深圳研究生院,信息安全中心,广东,深圳,518055)
A Collaborative Filtering Recommendation Algorithm Based on Cloud Model
ZHANG Guang-Wei,LI De-Yi,LI Peng,KANG Jian-Chu,CHEN Gui-Sheng
()
Abstract
Chart / table
Reference
Similar Articles
Article :Browse 4357   Download 4962
Received:May 18, 2006    Revised:February 05, 2007
> 中文摘要: 协同过滤系统是电子商务系统中最重要的技术之一,用户相似性度量方法是影响推荐算法准确率高低的关键因素.针对传统相似性度量方法存在的不足,利用云模型在定性知识表示以及定性、定量知识转换时的桥梁作用,提出一种在知识层面比较用户相似度的方法,克服了传统基于向量的相似度比较方法严格匹配对象属性的不足.以该方法为核心,在全面分析传统方法的基础上,提出一种新的协同过滤推荐算法.实验结果表明,算法在用户评分数据极端稀疏的情况下,仍能取得较理想的推荐质量.
中文关键词: 云模型  协同过滤  相似性  推荐系统  投票
Abstract:Recommendation system is one of the most important technologies applied in e-commerce. Similarity measuring method is fundamental to collaborative filtering algorithm,and traditional methods are inefficient especially when the user rating data are extremely sparse. Based on the outstanding characteristics of Cloud Model on the process of transforming a qualitative concept to a set of quantitative numerical values,a novel similarity measuring method,namely the likeness comparing method based on cloud model (LICM) is proposed in this paper. LICM compares the similarity of two users on knowledge level,which can overcome the drawback of attributes’ strictly matching. This work analysis traditional methods throughly and puts forward a novel collaborative filtering algorithm,which is based on the LICM method. Experiments on typical data set show the excellent performance of the present collaborative filtering algorithm based on LICM,even with extremely sparsity of data.
文章编号:     中图分类号:    文献标志码:
基金项目:Supported by the National Natural Science Foundation of China under Grant Nos.60496323, 60375016 (国家自然科学基金); the National Basic Research Program of China under Grant No.G2004CB719401 (国家重点基础研究发展计划(973)) Supported by the National Natural Science Foundation of China under Grant Nos.60496323, 60375016 (国家自然科学基金); the National Basic Research Program of China under Grant No.G2004CB719401 (国家重点基础研究发展计划(973))
Foundation items:
Reference text:

张光卫,李德毅,李鹏,康建初,陈桂生.基于云模型的协同过滤推荐算法.软件学报,2007,18(10):2403-2411

ZHANG Guang-Wei,LI De-Yi,LI Peng,KANG Jian-Chu,CHEN Gui-Sheng.A Collaborative Filtering Recommendation Algorithm Based on Cloud Model.Journal of Software,2007,18(10):2403-2411