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A Personalized Search Based on Context Related Models

机译:基于上下文相关模型的个性化搜索

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摘要

In recent years, with the rapid development of the World Wide Web, huge amount of data arises in our daily life. Which approach should be taken to assist users when searching the information they need is the point. For users, when facing the same resources, they more commonly annotate them or input search queries according to their own perspectives. This process has been already proven as a time-consuming. Based on the goal, we propose our methodology that to combine user's context, users' profile with users' Folksonomies together to optimize personal search. And at the end of this paper, we make an experiment to evaluate our methodology and which performs better.
机译:近年来,随着万维网的快速发展,我们的日常生活中出现了大量的数据。重点是当用户搜索所需信息时应采用哪种方法。对于用户来说,当面对相同的资源时,他们通常会根据自己的观点为它们添加注释或输入搜索查询。该过程已被证明是耗时的。基于该目标,我们提出了将用户的上下文,用户的个人资料与用户的个人分类法结合在一起以优化个人搜索的方法。并且在本文的最后,我们进行了一项实验,以评估我们的方法论,并且该方法效果更好。

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