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An adaptive method for organization name disambiguation with feature reinforcing

  • Fujitsu
  • School of Computer Science and Technology, Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Twitter is an online social networking, which has become an important source of information for marketing strategies and online reputation management. In this paper, we probe the problem of organization name disambiguation on twitter messages. This task is challenging due to the fact of lacking sufficient information both from organization and the tweets. We mine organization information from web sources to train a general classifier. Further, we mine tweets information. We train an adaptive classifier for a given organization name with more features derived from twitter messages labeled by the general classifier. The experiments on WePS-3 show mining web sources to enrich organization are effective. The adaptive classifier trained for a given organization is promising.

Original languageEnglish
Title of host publicationProceedings of the 26th Pacific Asia Conference on Language, Information and Computation, PACLIC 2012
Pages237-245
Number of pages9
StatePublished - 2012
Externally publishedYes
Event26th Pacific Asia Conference on Language, Information and Computation, PACLIC 2012 - Bali, Indonesia
Duration: 7 Nov 20127 Nov 2012

Publication series

NameProceedings of the 26th Pacific Asia Conference on Language, Information and Computation, PACLIC 2012

Conference

Conference26th Pacific Asia Conference on Language, Information and Computation, PACLIC 2012
Country/TerritoryIndonesia
CityBali
Period7/11/127/11/12

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