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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Zheng Xu Xiangfeng Luo Xiao Wei Lin Mei |
| Copyright Year | 2013 |
| Description | Author affiliation: Shanghai Univ., Shanghai, China (Xiangfeng Luo; Xiao Wei) || Third Res. Inst. of Minist. of Public Security, Shanghai, China (Zheng Xu; Lin Mei) |
| Abstract | Online popular events, which are constructed from news stories using the techniques of Topic Detection and Tracking (TDT), bring convenience to users who intend to see what is going on through the Internet. Recently, the web is becoming an important event information provider and poster due to its real-time, open, and dynamic features. However, it is difficult to detect events since the huge scale and dynamics of the internet. In this paper, we define the novel problem of investigating impact factors for event detection. We give the definitions of five impact factors including the number of increased web pages, the number of increased keywords, the number of communities, the average clustering coefficient, and the average similarities of web pages. These five impact factors contain statistic and content information of an event. Empirical experiments on real datasets including Google Zeitgeist and Google Trends show that that the number of web pages and the average clustering coefficient can be used to detect events. Some strategies integrating the number of web pages and the average clustering coefficient are also employed. The evaluations on real dataset show that the proposed function integrating the number of web pages and the average clustering coefficient can be used for event detection efficiently and correctly. |
| Starting Page | 580 |
| Ending Page | 587 |
| File Size | 653462 |
| Page Count | 8 |
| File Format | |
| ISBN | 9780769550961 |
| DOI | 10.1109/CSE.2013.92 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2013-12-03 |
| Publisher Place | Australia |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Context Google Event detection Communities web mining Web pages Web search Engines trends analysis |
| Content Type | Text |
| Resource Type | Article |
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