2023 4th International Conference on Computational Linguistics and Natural Language Processing (CLNLP 2023)

CLNLP 2023


Computational Linguistics



2023 International Conference on Computational Linguistics and Natural Language Processing (CLNLP 2023)-- Ei Compendex & Scopus—Call for paper  

August 18-20, 2023Nanjing, ChinaWebsite: www.clnlp.org

 

CLNLP 2023 welcomes researchers, engineers, scientists and industry professionals to an open forum where advances in the field of Computational Linguistics and Natural Language Processing can be shared and examined. The conference is an ideal platform for keeping up with advances and changes to a consistently morphing field. Leading researchers and industry experts from around the globe will be presenting the latest studies through papers and oral presentations. 

 

Publication and Indexing

Accepted and presented papers will be published in the digital conference proceedings which will submitted to Ei Compendex, Scopus, CPCI, Google Scholar and other major databases for index.

Excellent Papers from CLNLP 2023 will be recommended to be submitted for publication in journal.




Keynote Speakers

Prof. Haofen Wang——Tongji University, China

Prof. Huiyu Zhou——University of Leicester, UK

Prof. Yulan He——Kings College London, UK




Program Preview/ Program at a glance

August 18: Registration + Icebreaker Reception

August 19: Opening Ceremony+ KN Speech+ Technical Sessions

August 20: Technical Sessions+ Half day tour/Lab tours

 


Paper Submission

PDF version submit via CMT: https://cmt3.research.microsoft.com/CLNLP2023    

 


CONTACT US

Ms. Riva H. W. Wong

Email: mail@clnlp.org  

Website: 
www.clnlp.org

 

Topics of Interest

 

Computational Social Science and Cultural Analytics

Information extraction

Machine learning for NLP

Question Answering

Tagging, Chunking, Syntax and Parsing

Summarization

Semantics: lexical

NLP applications

Information retrieval and text mining

Natural language generation

Phonology, Morphology and Word Segmentation

Large-scale grammars of natural languages