%0 Conference Paper %1 so85507 %A Habib, Mena B. %A van Keulen, Dr.ir. Maurice %A Zhu, MSc. Zhemin %B 3rd workshop on Making Sense of Microposts, \MSM 2013 %C Brazil %D 2013 %I CEUR %K entitylinking microlink@l3s msm2013 %T Concept Extraction Challenge: University of Twente at \MSM2013 %U http://doc.utwente.nl/85507/ %X 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 YosefHBSW11 disambiguation system to disambiguate the extracted named entities and hence find their type.

@inproceedings{so85507, 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 \cite{YosefHBSW11} disambiguation system to disambiguate the extracted named entities and hence find their type. }, added-at = {2015-01-26T17:37:44.000+0100}, address = {Brazil}, author = {{Habib}, Mena B. and van {Keulen}, Dr.ir. Maurice and {Zhu}, MSc. Zhemin}, biburl = {https://www.bibsonomy.org/bibtex/2e0646764ec782ce243428da655eb77e7/asmelash}, booktitle = {3rd workshop on Making Sense of Microposts, \MSM 2013}, description = {Concept Extraction Challenge: University of Twente at #MSM2013 - UTpublications}, interhash = {8af0e9665b3e20486717c712b01464e9}, intrahash = {e0646764ec782ce243428da655eb77e7}, keywords = {entitylinking microlink@l3s msm2013}, month = may, publisher = {CEUR}, timestamp = {2015-01-26T17:37:44.000+0100}, title = {Concept Extraction Challenge: University of Twente at \MSM2013}, url = {http://doc.utwente.nl/85507/}, year = 2013 }