Maximum Entropy-Based Named Entity Recognition Method for Multiple Social Networking Services

Title
Maximum Entropy-Based Named Entity Recognition Method for Multiple Social Networking Services
Author(s)
정재은
Issue Date
201209
Publisher
NATL DONG HWA UNIV
Citation
JOURNAL OF INTERNET TECHNOLOGY, v.13, no.6, pp.931 - 937
Abstract
Given a certain question, named entity recognition (NER) methods are regarded as an efficient strategy to extract correct answers. The goal of this work is to extend such conventional NER methods for analyzing a set of microtexts of which lengths are relatively short. These microtexts are streaming through several different social networking services, e.g., Twitter and Face Book. To do so, we propose three heuristics for determining contextual associations between the microtexts, and discovering contextual clusters of microtexts, which can be expected to improve the performance of conventional NER tasks. Experimental results show the feasibility of the proposed mechanisms which extend the maximum entropy-based NER tasks for extracting relevant information in online social network applications.
URI
http://hdl.handle.net/YU.REPOSITORY/27279
ISSN
1607-9264
Appears in Collections:
공과대학 > 컴퓨터공학과 > Articles
Files in This Item:
There are no files associated with this item.
Export
RIS (EndNote)
XLS (Excel)
XML


qrcode

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

BROWSE