【摘要】 针对当前的搜索引擎提供面向查询、而非面向用户的服务,从而导致搜索引擎无法满足用户个性化的需求这一问题,提出了一种基于PLSA的新方法,将面向查询词的搜索转变成面向用户的搜索.首先,通过分析用户查询历史和浏览记录建立代表用户模型的用户兴趣向量,在用户发出查询时用户的查询词根据用户兴趣向量被映射到兴趣分类上,最终根据面向用户排序算法将返回结果列表重新排序.实验表明该面向用户搜索系统能够充分考虑用户的偏好,从而更好地满足不同用户的信息需求.更多还原

【Abstract】 In order to solve the problem that current search engines provide query-oriented searches rather than user-oriented ones,and that this improper orientation leads to the search engines’ inability to meet the personalized requirements of users,a novel method based on probabilistic latent semantic analysis(PLSA) is proposed to convert query-oriented web search to user-oriented web search.First,a user profile represented as a user’s topics of interest vector is created by analyzing the user’s click through data based on PLSA,then the user’s queries are mapped into categories based on the user’s preferences,and finally the result list is re-ranked according to the user’s interests based on the new proposed method named user-oriented PageRank(UOPR).Experiments on real life datasets show that the user-oriented search system that adopts PLSA takes considerable consideration of user preferences and better satisfies a user’s personalized information needs.更多还原