Search Engine User Behavior Analysis Based on Log Mining

With the growth in amount of search users,the behavior analysis has become one of the most important research issues for search engines in terms of architecture analysis,performance optimization and system maintenance.It is also a major area in both information retrieval and knowledge management.In order to better understand search behavior of web users,we analyzed web user behaviors based on 756 million entries of click-through logs.Several important aspects of user behaviors are studied,such as query length,ratio of query refining,query recommendation access,first/last click distribution,click number in query,et al.We also analyzed the differences in user behavior for different information needs based on separate query sets.These analyses may help improve both effectiveness and efficiency of search engines.