Paper Info
Title
EventSearch: a system for event discovery and retrieval on multi-type historical data
Abstract
We present EventSearch, a system for event extraction and retrieval on four types of news-related historical data, i.e., Web news articles, newspapers, TV news program, and micro-blog short messages. The system incorporates over 11 million web pages extracted from "Web InfoMall", the Chinese Web Archive since 2001. The newspaper and TV news video clips also span from 2001 to 2011. The system, upon a user query, returns a list of event snippets from multiple data sources. A novel burst model is used to discover events from time-stamped texts. In addition to offline event extraction, our system also provides online event extraction to further meet the user needs. EventSearch provides meaningful analytics that synthesize an accurate description of events. Users interact with the system by ranking the identified events using different criteria (scale, recency and relevance) and submitting their own information needs in different input fields.
Year
DOI
Venue
2012
10.1145/2339530.2339781
KDD
Keywords
Field
DocType
tv news program,multi-type historical data,web news article,online event extraction,offline event extraction,tv news video clip,event discovery,different criterion,chinese web archive,event extraction,web infomall,event snippet,web pages,information need
Data mining,World Wide Web,Information needs,Information retrieval,Web news,Ranking,Web page,Computer science,Complex event processing,WAR,Newspaper,Analytics
Conference
Citations 
PageRank 
References 
10
0.63
6
Authors
8
Name
Order
Citations
PageRank
Dongdong Shan11286.11
Wayne Xin Zhao2127566.73
Rishan Chen332617.81
Baihan Shu4231.67
Ziqi Wang5474.63
Junjie Yao626514.19
Hongfei Yan776335.67
Xiaoming Li8166992.16