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Named Entity Recognition for Short Text Messages

Author

Summary, in English

This paper describes a named entity recognition (NER) system for short text messages (SMS) running on a mobile platform. Most NER systems deal with text that is structured, formal, well written, with a good grammatical structure, and few spelling errors. SMS text messages lack these qualities and have instead a short-handed and mixed language studded with emoticons, which makes NER a challenge on this kind of material. We implemented a system that recognizes named entities from SMSes written in Swedish and that runs on an Android cellular telephone. The entities extracted are locations, names, dates, times, and telephone numbers with the idea that extraction of these entities could be utilized by other applications running on the telephone. We started from a regular expression implementation that we complemented with classifiers using logistic regression. We optimized the recognition so that the incoming text messages could be processed on the telephone with a fast response time. We reached an F-score of 86 for strict matches and 89 for partial matches. (C) 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of PACLING Organizing Committee.

Publishing year

2011

Language

English

Pages

178-187

Publication/Series

Computational Linguistics and Related Fields

Volume

27

Document type

Conference paper

Publisher

Elsevier

Topic

  • Computer Science

Keywords

  • Named entity recognition
  • Short text messages
  • SMS
  • Information
  • extraction
  • Ensemble systems

Conference name

Conference of the Pacific-Association-for-Computational-Linguistics (PACLING)

Conference date

2011-07-19 - 2011-07-21

Conference place

Kuala Lumpur, Malaysia

Status

Published

ISBN/ISSN/Other

  • ISSN: 1877-0428