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Key deadlines

Conference starts:

2024-07-19

Registration by:

2024-06-08

Early Bird Registration by:

2024-05-25

Paper Registration by:

2024-06-20

Paper Submission for Revision by:

2024-05-30

Paper Acceptance Notification by:

2024-06-19

Paper Final Submission by:

2024-07-10

Website

Visit the conference website

Conference Description

★2024 International Conference on Computational Linguistics and Natural Language Processing (CLNLP 2024)-- Ei Compendex & Scopus—Call for paper
July 19-21, 2024｜Yinchuan, China｜Website: www.clnlp.org

★CLNLP 2024 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 2024 will be recommended to be submitted for publication in journal.

★Program Preview/ Program at a glance
July 19: Registration + Icebreaker Reception
July 20: Opening Ceremony+ KN Speech+ Technical Sessions
July 21: Technical Sessions+ Half day tour/Lab tours

★Paper Submission
PDF version submit via CMT: https://cmt3.research.microsoft.com/User/Login?ReturnUrl=%2FCLNLP2024

★CONTACT US
Ms. Riva H. W. Wong
Email: [email protected]
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