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Clause Identification in English and Indian Languages: A Survey


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1 GZS Punjab Technical University, Bathinda, India
 

The problem of identification of clauses in natural language processing is to find away to identify the each type of clause, e.g., Dependent clause, independent clause. Clause identification plays very important role in preprocessing task for language processing activities. This paper reports about the Clause Identification proposed for various Languages like English, Malayalam, Bengali and Urdu. Various clause identification approaches like Hidden Markov Model (HMM), Support Vector Model (SVM), and Rule based approaches, Maximum Entropy (ME) and Conditional Random Field (CRF), Entropy Guided Transformation Learning (ETL), have been used for POS tagging.
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  • Clause Identification in English and Indian Languages: A Survey

Abstract Views: 171  |  PDF Views: 2

Authors

Misha Mittal
GZS Punjab Technical University, Bathinda, India
Abhilasha
GZS Punjab Technical University, Bathinda, India

Abstract


The problem of identification of clauses in natural language processing is to find away to identify the each type of clause, e.g., Dependent clause, independent clause. Clause identification plays very important role in preprocessing task for language processing activities. This paper reports about the Clause Identification proposed for various Languages like English, Malayalam, Bengali and Urdu. Various clause identification approaches like Hidden Markov Model (HMM), Support Vector Model (SVM), and Rule based approaches, Maximum Entropy (ME) and Conditional Random Field (CRF), Entropy Guided Transformation Learning (ETL), have been used for POS tagging.