Personalized information retrieval base-on user interest state

Zhanfang Chang, X. Ban, Yuan Yao, Binghu Chang, Di Wu
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引用次数: 1

Abstract

Different users have different needs, even the same user may have different desires in different time, Personalized Information Retrieval makes search results meet different users' information requirement. In this paper, a kind of user interest recognition algorithm is proposed, which can analyze the user interest state and identify the user's Temporary interest; And a state-based user interest model is developed, In this model, user interest is recognized by the algorithm mentioned above, and users' characteristic is extracted and Dynamic weighted, then gray relational analysis is introduced to for the comprehensive consideration of two aspects above. The experimental result indicates that the average push accuracy is above 70% and the push service is more accurate for the user who has a long interest cycle.
基于用户兴趣状态的个性化信息检索
不同的用户有不同的需求,甚至同一用户在不同的时间可能有不同的愿望,个性化信息检索使搜索结果满足不同用户的信息需求。本文提出了一种用户兴趣识别算法,该算法可以分析用户的兴趣状态,识别用户的临时兴趣;并建立了基于状态的用户兴趣模型,该模型采用上述算法识别用户兴趣,提取用户特征并进行动态加权,然后引入灰色关联分析,综合考虑上述两方面。实验结果表明,平均推送准确率在70%以上,对于兴趣周期较长的用户,推送服务更准确。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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