Abstract: A query weighted-based method is proposed for user modeling by simulating the interaction between user and search engine. First, the query log is divided into sessions according to the session division principle. Then, for each session, a group of user behavior information, such as query frequency, duration and the ranks of the clicked URLs, are employed to calculate the weight of queries. Finally, the voting method is used to generate user model. The experiment results show the effectiveness of the method over the AOL query log dataset.

Key words: user modeling, query log, session division, query weighted, user modeling, query log, session division, query weighted

摘要： 通过分析用户的查询日志, 模拟用户与搜索引擎之间的交互过程, 提出一种基于查询加权的用户建模方法。首先, 对查询日志进行会话分割; 然后, 利用会话中用户查询出现的次数、持续时间及所点击的URL排名等行为信息, 计算查询权重; 最后, 采用兴趣投票的方式, 完成用户模型的构建。在AOL (美国在线)查询日志数据集上的测试结果表明, 基于查询加权的用户建模方法在用户兴趣预测上取得较好的效果。

关键词: 用户建模, 查询日志, 会话分割, 查询加权, 用户建模, 查询日志, 会话分割, 查询加权