Abstract
We define and solve the problem of event detection and delineation as a task of identifying events and decomposing them to their major sub-events, with a description and a timeline. We propose DeLi, an algorithm that focuses on providing such an understanding of events and sub-events. DeLi, to the best of our knowledge, is the first method that addresses the problem in a generic stream of text, and in an online fashion. Extensive evaluation on social streaming data demonstrates that, by combining the structure of a social network with content attributes, our method outperforms the state-of-The-Art techniques.
Original language | English |
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Title of host publication | Proceedings - IEEE 34th International Conference on Data Engineering, ICDE 2018 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 1352-1355 |
Number of pages | 4 |
ISBN (Electronic) | 9781538655207 |
DOIs | |
Publication status | Published - 24 Oct 2018 |
Event | 34th IEEE International Conference on Data Engineering, ICDE 2018 - Paris, France Duration: 16 Apr 2018 → 19 Apr 2018 |
Conference
Conference | 34th IEEE International Conference on Data Engineering, ICDE 2018 |
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Country/Territory | France |
City | Paris |
Period | 16/04/18 → 19/04/18 |
Keywords
- Anomaly Detection
- Data Mining
- Event Detection
- Graph Mining
- Social Network Analysis
- Sub Event Detection
- Text Mining