Journal
EXPERT SYSTEMS WITH APPLICATIONS
Volume 39, Issue 9, Pages 8066-8070Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2012.01.136
Keywords
Named entity recognition; Social networks; Network analysis; Multiplex social network
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Funding
- National Research Foundation of Korea (NRF)
- Korea government (MEST) [2011-0017156]
- National Research Foundation of Korea [2011-0017156] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
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Named entity recognition (NER) methods have been regarded as an efficient strategy to extract relevant entities for answering a given query. The aim of this work is to exploit the conventional NER methods for analyzing a large set of microtexts of which lengths are short. Particularly, the microtexts are streaming on online social media, e.g., Twitter. To do so, this paper proposes three properties of contextual association among the microtexts to discover contextual clusters of the microtexts, which can be expected to improve the performance of NER tasks. As a case study, we have applied the proposed NER system to Twitter. Experimental results demonstrate the feasibility of the proposed method (around 90.3% of precision) for extracting relevant information in online social network applications. (C) 2012 Elsevier Ltd. All rights reserved.
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