DocumentCode
169563
Title
Bengali noun phrase chunking based on conditional random fields
Author
Sarkar, Kamal ; Gayen, Vivekananda
Author_Institution
Comput. Sci. & Eng. Dept., Jadavpur Univ., Kolkata, India
fYear
2014
fDate
9-11 Jan. 2014
Firstpage
148
Lastpage
153
Abstract
Noun phrase (NP) chunking deals with extracting the noun phrases from a sentence. While NP chunking is much simpler than parsing, it is still a challenging task to build an accurate and efficient NP chunker. Noun phrase chunking is an important and useful task in many natural language processing applications. It is studied well for English, however not much work has been done for Bengali. This paper presents a Bengali noun phrase chunking approach based on conditional random fields (CRFs) models. Our developed NP chunker has been tested on the ICON 2013 dataset and achieves an impressive F-score of 95.92.
Keywords
natural language processing; Bengali noun phrase chunking; CRF; English; F-score; ICON 2013 dataset; NP chunker; conditional random fields; natural language processing applications; Artificial neural networks; Computers; Decoding; Training; Vocabulary; Bengali Language; CRF; Conditional Random Fields; Information Overload Problem; Noun Phrase Chunking;
fLanguage
English
Publisher
ieee
Conference_Titel
Business and Information Management (ICBIM), 2014 2nd International Conference on
Conference_Location
Durgapur
Print_ISBN
978-1-4799-3263-4
Type
conf
DOI
10.1109/ICBIM.2014.6970957
Filename
6970957
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