About the Journal
The Edinburgh Journal of Natural Language Processing and AI (EJNLPAI) is a peer-reviewed, open-access academic journal that provides a specialized platform for advanced research in natural language processing (NLP), computational linguistics, and artificial intelligence. Established in 2017 and published annually from Edinburgh, Scotland, EJNLPAI curates high-impact scholarship ranging from foundational NLP theories to cutting-edge AI applications in text analytics, language generation, semantic modeling, and conversational agents. It supports multidisciplinary work that bridges linguistics, deep learning, cognitive computing, and AI ethics. The journal adheres to a rigorous double-blind peer review process and global editorial standards.
Journal Snapshot
Journal Name: Edinburgh Journal of Natural Language Processing and AI (EJNLPAI)
ISSN: 2789-5627
Impact Factor: 5.8 (By ResearchBib)
Journal Initials: EJNLPAI
Research Scope: NLP, Computational Linguistics, Machine Translation, Text Analytics, AI in Language Understanding, Language Modeling, Conversational AI, Cognitive Computing
Publication Mode: Digital (On this Website)
Frequency: Annual (1 Volume per Year)
Launch Year: 2017
Review Mode: Double Blind Peer Review
Plagiarism Allowed: 10% (as per Turnitin)
Coverage: UK and Global
Language: English
Current Issue
We are pleased to present the latest volume of the Edinburgh Journal of Natural Language Processing and AI (EJNLPAI). This issue highlights the latest developments in NLP, machine translation, and intelligent language systems. With contributions from global scholars, this edition bridges theoretical discourse and practical innovation in computational linguistics, deep learning for language understanding, and AI-driven human-computer interaction. EJNLPAI remains committed to fostering interdisciplinary research that reflects the evolving intersection of AI and human language. Each article published herein contributes to redefining how machines process, understand, and generate human language.
