Improving named entity recognition for morphologically rich languages using word embeddings

Proceedings - 2014 13th International Conference on Machine Learning and Applications, ICMLA 2014

Volumn , Issue , 2014, Pages 117-122

  Demir, Hakan ^a   Ozgur, Arzucan ^b  

^a SCIENTIFIC AND TECHNOLOGICAL RESEARCH COUNCIL OF TURKEY   (Turkey)

^b BOGAZICI UNIVERSITY   (Turkey)

Author keywords

Czech NER; Named Entity Recognition; Skip gram; Turkish NER; Word Embeddings

Indexed keywords

ARTIFICIAL INTELLIGENCE; LEARNING ALGORITHMS; LEARNING SYSTEMS; SUPERVISED LEARNING;

CZECH NER; EMBEDDINGS; NAMED ENTITY RECOGNITION; SKIP-GRAM; TURKISHS;

COMPUTATIONAL LINGUISTICS;

EID: 84946686070     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICMLA.2014.24     Document Type: Conference Paper

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