【摘要】 会话识别是Web日志挖掘的关键步骤,然而很多方法所得到的会话不够精确。针对Web日志挖掘中的会话识别问题,在最常用的Timeout方法的基础上,提出了一种改进的基于平均时间阈值的识别方法。通过动态计算会话中请求记录间的平均时间间隔,个性化地调整页面的时间阈值,相对于传统的对所有用户页面使用单一的先验阈值,该方法能够更准确地识别出长对话。最后对生成的侯选会话集进行二次识别,使识别出的会话更为合理有效。实验结果表明,会话质量得到了提高。更多还原

【Abstract】 Although session identification is an important step in web log mining,the session identified by existing methods are not ac-curate.Toward session identification in web log mining,an access timeout-based improvement is carried out of session identification in web log mining.By calculating the average intervals dynamically among request records in the session,adjusting a threshold individually.Compared to the traditional method that defines a uniform threshold for all web pages experimentally,the approach presents can identify the long session more accurately.Then generating sets of candidate session is re-identified,which make the session more reasonable and effective.The quality of session identification is proved more efficiency by experiments.更多还原