We use a semi-supervised approach which uses a small annotated corpus and a large raw corpus for the Hindi NER task using maximum entropy classifier. A novel ...
We use a semi-supervised approach which uses a small anno- tated corpus and a large raw corpus for the Hindi NER task using maxi- mum entropy classifier. A ...
A semi-supervised approach which uses a small annotated corpus and a large raw corpus for the Hindi NER task using maximum entropy classifier and a novel ...
Sujan Kumar Saha , Pabitra Mitra, Sudeshna Sarkar : A Semi-supervised Approach for Maximum Entropy Based Hindi Named Entity Recognition. PReMI 2009: 225-230.
A Semi-supervised Approach for Maximum Entropy Based Hindi Named Entity Recognition. PReMI '09: Proceedings of the 3rd International Conference on Pattern ...
A Semi-supervised Approach for Maximum Entropy Based Hindi Named Entity Recognition · hmtl icon · Sujan Kumar Saha, Pabitra Mitra, Sudeshna Sarkar. Published: ...
This thesis describes a novel statistical named-entity (ie “proper name”) recognition system known as “MENE” (Maximum Entropy Named Entity).
Abstract Machine learning based approach for Named Entity Recognition (NER) requires sufficient annotated corpus to train the classifier.
(PDF) Maximum Entropy Approach for Named Entity Recognition in ...
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PDF | This paper reports about the development of a Named Entity Recognition (NER) system in two leading Indian languages, namely Bengali and Hindi.
A semi-supervised approach which uses a small annotated corpus and a large raw corpus for the Hindi NER task using maximum entropy classifier and a novel ...