基于内容过滤的个性化搜索算法  

A Personalized Search Algorithm by Using Content-Based Filtering

作　　者：曾春[1] 邢春晓[1] 周立柱[1] 

机构地区：[1]清华大学计算机科学与技术系,北京100084

出　　处：《软件学报》2003年第5期999-1004,共6页Journal of Software

基　　金：国家自然科学基金;国家重点基础研究发展规划(973)~~

摘　　要：传统信息检索技术满足了人们一定的需要,但由于其通用的性质,仍然不能满足不同背景、不同目的和不同时期的查询请求.提出了一种基于内容过滤的个性化搜索算法.利用领域分类模型上的概率分布表达了用户的兴趣模型,然后给出了相似性计算和用户兴趣模型更新的方法.对比实验表明,概率模型比矢量空间模型更好地表达了用户的兴趣和变化.Traditional information retrieval technologies satisfy users need to a great extent. However, for their all-purpose characteristics, they can not satisfy any query from the different background, with the different intention and at the different time. A personalized search algorithm by using content-based filtering is presented in this paper. The user model is represented as the probability distribution over the domain classification model. A method of computing similarity and a method of revising user model are provided. Compared with the vector space model, the probability model is more effective on describing a users interests.

关 键 词：个性化搜索算法 内容过滤 用户模型 计算机网络 信息检索 兴趣模型 

分 类 号：TP393[自动化与计算机技术—计算机应用技术] G354.4[自动化与计算机技术—计算机科学与技术]