基于群体智慧的Web访问日志会话主题识别研究  

Swarm Intelligence Based Topic Identification for Sessions in Web Access Log

作　　者：方奇[1] 刘奕群[1] 张敏[1] 茹立云[1] 马少平[1] 

机构地区：[1]智能技术与系统国家重点实验室,清华信息科学与技术国家实验室(筹),清华大学计算机系,北京100084

出　　处：《中文信息学报》2011年第1期35-40,共6页Journal of Chinese Information Processing

基　　金：自然科学基金资助项目(60736044,60903107);高等学校博士学科点专项科研基金资助项目(20090002120005)

摘　　要：Web访问日志中的会话(session)是指特定用户在一定时间范围内的访问行为的连续序列。会话主题(topic)是指会话中具有相同用户意图的部分。从会话中进一步识别出能体现用户意图的处理单元(topic)是进行用户访问行为分析的重要基础。目前相关工作主要集中在边界识别上,无法处理用户意图交叉情况。为了解决该问题,该文重新形式化定义了session和topic的相关概念,提出最大划分的求解任务,并设计出了基于用户群体智慧的会话主题识别算法。在使用大规模真实Web访问日志的实验中,我们的算法取得了不错的效果。A session in Web access log denotes a continuous-time sequence of user＇s Web browsing behavior.A topic of a session represents a hidden browsing intent of a Web user.It is fundamental to identify several topic-based log units from a session.Existing work mainly focuses on detecting boundaries without considering the common situation in which different topics often overlap in one session.In this paper,we first re-define the concept of session and topic,and then the task of largest segmentation is proposed.We further design the session topic identification algorithm based on crowd wisdom of Web users.The effectiveness of the algorithm is validated by the experiments performed on large scale of realistic Web access logs.

关 键 词：会话主题识别 WEB访问日志 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]