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中文摘要：
为克服语言歧义性和用户使用简短查询语句的习惯对搜索引擎查询准确率造成的影响,提出了一种基于偏好的查询扩展方法。该方法将用户对网页的偏好转化为对知识库中概念的偏好,建立用户兴趣模型,在该模型基础上对原始查询结果进行分析,挑选出与用户偏好关联最紧密的关键词加入原查询,解决了基于局部分析的查询扩展方法在初次检索质量不高时性能恶化的问题。实验表明,本文提出的方法相对于传统的查询扩展算法可以大幅度提高查询精度。
英文摘要：
To solve the problems of polysemy and short query that affect the precision of the search engines, this paper proposes a query expansion scheme based on user profiles. This schema gains the users＇ interests in web pages, and classifies these web pages into conceptions in knowledge base to create user profiles about users＇ interests in these conceptions： Based on user profiles, the terms which are most related to user interests are selected as expansion terms. This scheme can overcome the drawback of local analysis that the effects of expanded query strongly depend on the quality of the initial retrieval. The experimental results show that the proposed query expansion scheme can achieve significant improvements in retrieval effectiveness compared to current query expansion techniques.
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