Concept Extraction Challenge: University of Twente at #MSM2013

Mena Badieh Habib, Maurice van Keulen, Zhemin Zhu

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

10 Citations (Scopus)
51 Downloads (Pure)


Twitter messages are a potentially rich source of continuously and instantly updated information. Shortness and informality of such messages are challenges for Natural Language Processing tasks. In this paper we present a hybrid approach for Named Entity Extraction (NEE) and Classification (NEC) for tweets. The system uses the power of the Conditional Random Fields (CRF) and the Support Vector Machines (SVM) in a hybrid way to achieve better results. For named entity type classification we used AIDA disambiguation system to disambiguate the extracted named entities and hence find their type.
Original languageUndefined
Title of host publicationProceedings of the Concept Extraction Challenge at the Workshop on 'Making Sense of Microposts'
Place of PublicationAachen, Germany
Number of pages4
Publication statusPublished - May 2013
Event3rd workshop on Making Sense of Microposts, #MSM 2013 - Rio de Janeiro, Brazil
Duration: 13 May 201313 May 2013

Publication series

NameCEUR Workshop Proceedings
ISSN (Print)1613-0073


Workshop3rd workshop on Making Sense of Microposts, #MSM 2013
Other13 May 2013


  • METIS-296393
  • Named Entity RecognitionNamed Entity LinkingNamed Entity ExtractionNamed Entity DisambiguationTwitterTweetsMicroblogs
  • IR-85507
  • EWI-23249

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