Online named entity recognition method for microtexts in social networking services: A case study of twitter

Title
Online named entity recognition method for microtexts in social networking services: A case study of twitter
Author(s)
정재은
Keywords
MAXIMUM-ENTROPY
Issue Date
201207
Publisher
PERGAMON-ELSEVIER SCIENCE LTD
Citation
EXPERT SYSTEMS WITH APPLICATIONS, v.39, no.9, pp.8066 - 8070
Abstract
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.
URI
http://hdl.handle.net/YU.REPOSITORY/27620http://dx.doi.org/10.1016/j.eswa.2012.01.136
ISSN
0957-4174
Appears in Collections:
공과대학 > 컴퓨터공학과 > Articles
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