CAJ | 학술논문

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。
침대목전주류수색인경개성화정도저적문제，통과분석용호적류람행위화류람내용래획취용호적흥취유별이급관건사，용일조대권중적관건사조성적향량집래표시용호흥취모형，이용경신산법대모형진행경신여우화。장용호흥취모형여개원수색인경Nutch상결합，가입중문분사조건IKAnalyzer，실현료개성화수색인경。진행료전통수색화개성화수색대비실험，결과증명，Nutch개성화수색인경결과경부합용호흥취。
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.