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Bengali Named Entity Recognition Using Margin Infused Relaxed Algorithm

  • Somnath Banerjee
  • Sudip Kumar Naskar
  • Sivaji Bandyopadhyay
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8655)

Abstract

The present work describes the automatic recognition of named entities based on language independent and dependent features. Margin Infused Relaxed Algorithm is applied for the first time in order to learn named entities for Bengali language. We used openly available annotated corpora with twelve different tagset defined in IJCNLP-08 NERSSEAL shared task and obtained 91.23%, 87.29% and 89.69% precision, recall and F-measure respectively. The proposed work outperforms the existing models with satisfactory margin.

Keywords

Support Vector Machine Target Word Natural Language Processing Conditional Random Field Name Entity Recognition 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Somnath Banerjee
    • 1
  • Sudip Kumar Naskar
    • 1
  • Sivaji Bandyopadhyay
    • 1
  1. 1.Department of Computer Science and EngineeringJadavpur UniversityIndia

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