利用用户历史进行个性化信息检索

Taehwan Kim, Hochul Jeon, Joongmin Choi
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引用次数: 6

摘要

许多研究人员已经在万维网上实现了许多搜索算法。最好的算法之一是使用PageRank技术的谷歌。PageRank方法计算每个文档的Mink个数,然后按照Mink成员的顺序对文档进行排序。但是很难找到用户需要的结果,因为这种方法找到的文件不是对个人有价值的,而是对公众有价值的。本文提出了一种个性化的搜索引擎,它既强调页面排名等公共价值,又强调个人价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Personalized Information Retrieval Using the User History
Many search algorithms have been implemented by many researchers on the world wide web. One of the best algorithms is Google using PageRank technology. PageRank approach computes the number of Mink of each documents then ranks documents in the order of Mink members. But it is difficult to find the results that user needs, because this method finds documents not valueable for a person but valueable for the public. This paper proposes a personalized search engine that emphasizes both the public worth such as page rank using the Mink of each documents and the personal worth.
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