Title
Detecting hot events from web search logs
Abstract
Detecting events from web resources is a challenging task, attracting many attentions in recent years. Web search log is an important data source for event detection because the information it contains reflects users' activities and interestingness to various real world events. There are three major issues for event detection from web search logs: effectiveness, efficiency and the organization of detected events. In this paper, we develop a novel Topic and Event Detection method, TED, to address these issues. We first divide the whole data into topics for efficiency consideration, and then incorporate link information, temporal information and query content to ensure the quality of detected events. Finally, events detected are organized through the proposed interestingness measure as well as topics they belong to. Experiments are conducted on a commercial search engine log. The results demonstrate that our method can effectively and efficiently detect hot events and give a meaningful organization of them.
Year
DOI
Venue
2010
10.1007/978-3-642-14246-8_41
WAIM
Keywords
Field
DocType
temporal information,commercial search engine log,hot event,web resource,link information,event detection,efficiency consideration,event detection method,web search log,detecting event,search engine
Web resource,Data source,Data mining,World Wide Web,Search engine,Information retrieval,Computer science
Conference
Volume
ISSN
ISBN
6184
0302-9743
3-642-14245-1
Citations 
PageRank 
References 
2
0.36
19
Authors
7
Name
Order
Citations
PageRank
Yingqin Gu1192.37
Jianwei Cui2273.37
Hongyan Liu351746.49
Xuan Jiang420.36
Jun He523019.86
Xiaoyong Du6882123.29
Zhixu Li721043.55