liu.seSearch for publications in DiVA
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Named Entity Recognition for Short Text Messages
Lund University, Lund, Sweden.
Lund University, Lund, Sweden.
Sony Ericsson, Lund, Sweden.
Lund University, Lund, Sweden.
2011 (English)In: Procedia - Social and Behavioral Sciences, ISSN 1877-0428, E-ISSN 1877-0428, Vol. 27, no Pacling, 178-187 p.Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Elsevier, 2011. Vol. 27, no Pacling, 178-187 p.
Keyword [en]
ensemble systems, information extraction, named entity recognition, short text messages, sms
National Category
Computer and Information Science
Identifiers
URN: urn:nbn:se:liu:diva-91230DOI: 10.1016/j.sbspro.2011.10.596OAI: oai:DiVA.org:liu-91230DiVA: diva2:616532
Available from: 2013-04-17 Created: 2013-04-17 Last updated: 2017-12-06Bibliographically approved

Open Access in DiVA

fulltext(1078 kB)489 downloads
File information
File name FULLTEXT03.pdfFile size 1078 kBChecksum SHA-512
829c0319be9d41e1a423ba5cec39dd834710115e90c4c2c2a6e16e976f27ed2a14ff5614a29284485820b1976b4d309114e47929b7fba4914af7ea1ff7383c01
Type fulltextMimetype application/pdf

Other links

Publisher's full text

Authority records BETA

Kirkegaard, Camilla

Search in DiVA

By author/editor
Kirkegaard, Camilla
In the same journal
Procedia - Social and Behavioral Sciences
Computer and Information Science

Search outside of DiVA

GoogleGoogle Scholar
Total: 489 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 154 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf