摘要
针对目前主流搜索引擎个性化程度低的问题,通过分析用户的浏览行为和浏览内容来获取用户的兴趣类别以及关键词,用一组带权重的关键词组成的向量集来表示用户兴趣模型,利用更新算法对模型进行更新与优化。将用户兴趣模型与开源搜索引擎Nutch相结合,加入中文分词组件IKAnalyzer,实现了个性化搜索引擎。进行了传统搜索和个性化搜索对比实验,结果证明,Nutch个性化搜索引擎结果更符合用户兴趣。
In order to improve the degree of personalization for popular search engine, the user＇s interest categories and keywords were got by analyzing user＇s browsing behavior and content. User profile was represented by a vector set which consisted of a set of weighted keywords and updated by correlated algorithm. By embedding in user profile and IKAnalyzer, Nutch became a personalized search engine. Comparative experiments were carried out with the traditional search and the personalized search. The results show that, the personalized search engine got more relevant result with user interest than traditional research engine and was proved to be effective.
出处
《计算机时代》
2015年第9期26-28,32,共4页
Computer Era
基金
湖南省教育科学"十二五"规划2013年度课题(XJK013BXX002)
