@inproceedings{44970df51f6146b88071d59664b0b96c,
title = "Concept Extraction Challenge: University of Twente at #MSM2013",
abstract = "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.",
keywords = "METIS-296393, Named Entity RecognitionNamed Entity LinkingNamed Entity ExtractionNamed Entity DisambiguationTwitterTweetsMicroblogs, IR-85507, EWI-23249",
author = "Habib, {Mena Badieh} and {van Keulen}, Maurice and Zhemin Zhu",
note = "This paper won the Best Challenge Submission. By accident, the name of author Zhemin Zhu is missing on the official paper in the proceedings although he is an authentic author for the paper. The PDF attached here includes him.; null ; Conference date: 13-05-2013 Through 13-05-2013",
year = "2013",
month = may,
language = "Undefined",
series = "CEUR Workshop Proceedings",
publisher = "CEUR",
pages = "17--20",
booktitle = "Proceedings of the Concept Extraction Challenge at the Workshop on 'Making Sense of Microposts'",
}