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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Chun-Shuo Lin Meng-Fen Chiang Wen-Chih Peng Chien-Cheng Chen |
| Copyright Year | 2011 |
| Description | Author affiliation: National Chiao Tung University, Hsinchu, Taiwan, ROC (Chun-Shuo Lin; Meng-Fen Chiang; Wen-Chih Peng) || Chunghwa Telecom Labs, Taoyuan, Taiwan, ROC (Chien-Cheng Chen) |
| Abstract | A point of interest (POI) is a location that users can find something interesting. The POI information is typically made by the POI service provider and users can also add comments to a POI or add a new POI to enrich the POI contents. However, the information does not update frequently and some new points or time-sensitive events may not be marked in the POI service. Therefore, we construct a framework to extract the events from microblog to support an event-based POI service different from traditional POI service. With this kind of application, users can easily to get the events around them. In Web 2.0, microblog has become an important media spreading information in the web. With the help of mobile devices, microblogs can spread the information with greater spatiotemporal sensitivity. We take the spatial and temporal features of messages in microblogs to detect spatiotemporal events and use it to enrich POI service. This work aims at detecting spatiotemporal events in microblogs with an pair {location, time} from an handset device and feedbacks information to the users. To achieve this goal, we propose a framework with 4 phases: (1) profile construction; (2) feature extraction; (3) event summary detection; (4) ranking events. In this paper, we propose STF(standing for Spatio-Temporal Focus) value to evaluate the distinctiveness of a feature. Furthermore, we combine STF value with document overlap to expand an event cluster from an event seed. To extract the top-k possible event summaries, an efficient top-k soft clustering algorithm is proposed in this paper. In the experiments, we use real data set from Twitter to verify our proposed framework. |
| Starting Page | 1 |
| Ending Page | 4 |
| File Size | 442953 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781457716683 |
| e-ISBN | 9781457716706 |
| DOI | 10.1109/APNOMS.2011.6076994 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-09-21 |
| Publisher Place | Taiwan |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Google Event detection Semantics Clustering algorithms Feature extraction Spatiotemporal phenomena Web sites |
| Content Type | Text |
| Resource Type | Article |
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