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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:本文在Web Log Mining中获取会话标识作为研究对象,提出了一种基于平均时间阈值的改进算法。通过在会话中的请求记录中动态计算平均间隔,单独调整时间阈值,并与定义所有用户网页的统一阈值的传统算法进行比较,本文中的算法可以识别更多的时间准确。最后,该算法重新标识生成的候选会话集,这使得识别的会话更合理和有效。实验结果表明会话鉴定质量得到改善。

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