Natural Language Processing: State of The Art, Current Trends and Challenges
2017/08/17 by Diksha Khurana, Aditya Koli, Kiran Khatter +1 · 30 citations
Computer Science · #Natural Language Processing Techniques #Text and Document Classification Technologies #Topic Modeling #cs.CL
paper · pdf · doi:10.1007/s11042-022-13428-4
published as Multimed Tools Appl (2022) · 25 pages
arxiv created 2017/08/17 · crossref issued 2022/07/14 · crossref published 2022/07/14 · crossref published-online 2022/07/14 · openalex publication_date 2022/07/14 · crossref created 2022/07/14 · arxiv updated 2022/08/01 · crossref published-print 2023/01/01 · crossref deposited 2025/04/09 · openalex created_date 2025/10/10 · crossref indexed 2026/07/30 · openalex updated_date 2026/08/04
Abstract
Natural language processing (NLP) has recently gained much attention for representing and analysing human language computationally. It has spread its applications in various fields such as machine translation, email spam detection, information extraction, summarization, medical, and question answering etc. The paper distinguishes four phases by discussing different levels of NLP and components of Natural Language Generation (NLG) followed by presenting the history and evolution of NLP, state of the art presenting the various applications of NLP and current trends and challenges.
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