Word-Representation-Based Method for Extracting Organizational Events from Online Media
Online social media exhibit massive organizational event relevant messages, and the well categorized event information can be useful in many real-world applications. In this paper, we propose a research framework to extract high quality event information from massive online media data. The main cont...
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| Veröffentlicht in: | 电子科技学刊 2017-12, Vol.15 (4), p.407-412 |
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| container_title | 电子科技学刊 |
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| creator | Jun-Qiang Zhang Xiong-Wen Deng Yu Qian |
| description | Online social media exhibit massive organizational event relevant messages, and the well categorized event information can be useful in many real-world applications. In this paper, we propose a research framework to extract high quality event information from massive online media data. The main contributions lie in two aspects: First, we present an event-extraction and event-categorization system for online media data; second, we present a novel approach for both discovering important event categories and classifying extracted events based on word representation and clustering model. Experimental results with real dataset show that the proposed framework is effective to extract high quality event information. |
| doi_str_mv | 10.11989/JEST.1674-862X.602061 |
| format | Article |
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| identifier | ISSN: 1674-862X |
| ispartof | 电子科技学刊, 2017-12, Vol.15 (4), p.407-412 |
| issn | 1674-862X |
| language | eng |
| recordid | cdi_wanfang_journals_zgdzkj_e201704012 |
| source | Alma/SFX Local Collection |
| subjects | detection social Event media text mining word representation |
| title | Word-Representation-Based Method for Extracting Organizational Events from Online Media |
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