Bengali Noun Phrase Chunking Based on Conditional Random Fields

被引：0
|
作者：
Sarkar, Kamal [1 ]
Gayen, Vivekananda [2 ]
机构：
[1] Jadavpur Univ, Dept Comp Sci & Engn, Kolkata 700032, India
[2] Cent Calcutta Polytech, Comp Sci & Technol Dept, Kolkata 700014, India
来源：
2014 2ND INTERNATIONAL CONFERENCE ON BUSINESS AND INFORMATION MANAGEMENT (ICBIM) | 2014年
关键词：
Noun Phrase Chunking; CRF; Conditional Random Fields; Bengali Language; Information Overload Problem;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
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.
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页数：6
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