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Session Identification Algorithm for Web Log Mining

机译:Web日志挖掘的会话识别算法

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This paper takes session identification in web log mining as research object, proposes an improved algorithm based on average time threshold value. By calculating the average intervals dynamically among request records in the session, adjusting the time threshold value individually, and compared to the traditional algorithm that defines a uniform threshold value for all users' web pages, the algorithm in this paper can identify the long session more accurately. At last, the algorithm re-identifies the generated sets of candidate session, which make the identified session more reasonable and effective. Experiment result shows that the quality of session identification is improved.
机译:本文以Web日志挖掘中的会话识别为研究对象,提出了一种基于平均时间阈值的改进算法。通过动态计算会话中请求记录之间的平均间隔,分别调整时间阈值,并与为所有用户网页定义统一阈值的传统算法相比,本文中的算法可以识别更长的会话准确。最后,该算法重新识别生成的候选会话集,这使得所识别的会话更加合理和有效。实验结果表明,会话识别的质量得到了提高。

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