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IJNLC 2021 : International Journal on Natural Language Computing

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Link: http://airccse.org/journal/ijnlc/index.html
 
When N/A
Where N/A
Submission Deadline Jan 23, 2021
Notification Due Feb 23, 2021
Final Version Due Mar 3, 2021
Categories    natural language processing   NLP   ontology   text mining
 

Call For Papers

International Journal on Natural Language Computing (IJNLC)

Citations, h-index, i10-index of IJNLC

Scope and Topics

Natural Language Processing is a programmed approach to analyze text that is based on both a set of theories and a set of technologies. This forum aims to bring together researchers who have designed and build software that will analyze, understand, and generate languages that humans use naturally to address computers.

Topics of interest include but are not limited to, the following

  • Phonology, Morphology
  • Chunking/Shallow Parsing
  • Parsing/Grammatical Formalisms
  • Semantic Processing
  • Lexical Semantics
  • Ontology
  • Linguistic Resources
  • Statistical and Knowledge based methods
  • POS tagging
  • Discourse
  • Paraphrasing/Entailment/Generation
  • Machine Translation
  • Information Retrieval
  • Text Mining
  • Information Extraction
  • Question Answering
  • Dialog Systems
  • Spoken Language Processing
  • Speech Recognition and Synthesis

Paper Submission

Authors are invited to submit papers for this journal through E-mail  ijnlcjournal@airccse.org or through Submission System. Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal.

Important Dates

 

Submission Deadline:January 23, 2021
Authors Notification:February 23, 2021
Final Manuscript Due:March 03, 2021
Publication Date:Determined by the Editor-in-Chief

Current Issue


December 2020, Volume 9, Number 6

Automatic Arabic Named Entity Extraction and Classification for Information Retrieval   Full Text
Omar ASBAYOU, Lumière Lyon 2 University, France

Dutch Named Entity Recognition and De-Identification Methods for the Human Resource Domain   Full Text
Chaïm van Toledo, Friso van Dijk, and Marco Spruit, Utrecht University, Netherlands

Editor In Chief


Editorial Board Members

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