User Profile for Personalized Web Search

摘要：

Different users usually have different special information needs when they use search engines to find web information. The technologies of personalized web search can be used to solve the problem. An effective way to personalized search engines results is to construct user profile to present an individual users preference. Utilizing the relative machine learning techniques, three approaches are proposed to build the user profile in this paper. These approaches are called as Rocchio method, k-Nearest Neighbors method and Support Vector Machines method. Experimental results based on a constructed dataset show that k-Nearest Neighbors method is better than others for its efficiency and robustness.

关键词： personalized web search search engine user profile k-Nearest Neighbors support vector machines

作者: Chunyan Liang

作者单位: School of Economics and Management North China Electric Power University Beijing, China

会议类型: 国际会议

会议名称: 2011 Eighth International Conference on Fuzzy System and Knowledge Discovery(第八届模糊系统与知识发现国际会议 FSKD 2011)

会议地点: 上海

会议语种:英文

页码: 1897-1900

在线出版日期: 2011-07-26（万方平台首次上网日期，不代表论文的发表时间）