Call for Papers - International Journal of Computational Linguistics (IJCL)

IJCL 2020


Data Mining & Analysis Databases & Information Systems





Computational linguistics is an interdisciplinary field dealing with the statistical and/or rule-based modeling of natural language from a computational perspective. Today, computational language acquisition stands as one of the most fundamental, beguiling, and surprisingly open questions for computer science.
International Journal of Computational Linguistics (IJCL) is a peer review open access bi-monthly journal providing a scientific forum where computer scientists, experts in artificial intelligence, mathematicians, logicians, cognitive scientists, cognitive psychologists, psycholinguists, anthropologists and neuroscientists can present research and experimental studies. The journal publishes papers that describe state-of-the-art techniques, scientific research studies and results in computational linguistics in general but computational models, corpus linguistics, computational theories, information retrieval and extraction, linguistics modeling techniques, linguistics theories, machine translation, natural language processing, quantitative linguistics, speech analysis and speech recognition in particular.
IJCL invite linguistic specialists, researchers and scientists from different domains to share their understanding and contributions towards linguistics that set scientific objectives and demonstrate the operation of new methods in the field of computational linguistics.
LIST OF TOPICS
§ Comparative Surveys that Critique Previously reported
§ Computational Linguistics
§ Computational Models
§ Computational Theories
§ Corpus Linguistics
§ Formal Linguistics-Theoretic and Grammar Induction
§ Information Retrieval and Extraction
§ Language Generation
§ Language Learning
§ Linguistics Modeling Techniques
§ Linguistics Theories
§ Machine Translation
§ Models that Address the Acquisition of Word-order
§ Models that Combine Linguistics Parsing
§ Models that Employ Statistical/probabilistic Grammar
§ Models that Employ Techniques from machine learning
§ Natural Language Processing
§ Quantitative Linguistics
§ Speech Analysis/Synthesis
§ Speech Recognition/Understanding
§ Spoken Dialog Systems
§ Web Information Extraction/Mining
EDITORIAL BOARD MEMBERS
§ Dr. Michal Ptaszynski - Hokkai-Gakuen University (Japan)
§ Dr. Pascaline Merten - HEB-ISTI (Belgium)
§ Dr. Pawel Dybala - Otaru University of Commerce (Japan)
§ Dr. John Hanhong LI - The Hong Kong Polytechnic University (China)
§ Dr. Stephen Doherty - Dublin City University (Ireland)
§ Dr. M. Zakaria Kurdi - University of Lynchburg, US, VA (United States of America)