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CALL FOR PAPERS

Special Issue on Current Approaches and Applications in Natural Language Processing

Applied Sciences. MDPI Open Access Journal
JCR Impact Factor: 2.474 (Q2 in Engineering, multidisciplinary, 2019)

Deadline for manuscript submissions: 20 September 2021.

**** Special issue information

Dear colleague,

We’re glad to invite you to submit a paper to the special issue on “Current Approaches and Applications in Natural Language Processing”, for the open access journal Applied Sciences.

Current approaches in Natural Language Processing (NLP) have shown impressive improvements in many major tasks: machine translation, language modelling, text generation, sentiment/emotion analysis, natural language understanding, question answering,
among others. The advent of new methods and techniques like graph-based approaches, reinforcement learning or deep learning have boosted many of the tasks in NLP to reach human-level (and even further) performance. This has attracted the interest of many
companies, so new products and solutions can profit from the advances of this relevant area within the artificial intelligence domain.

This Special Issue focuses on emerging techniques and trendy applications of NLP methods is an opportunity to report on all these achievements, establishing a useful reference for industry and researchers on cutting edge human language technologies.
Given the focus of the journal, we expect to receive works that propose new NLP algorithms and applications of current and novel NLP tasks. Also, updated overviews on the given topics will be considered, identifying trends, potential future research
areas and new commercial products.

**** Topics of interest

The topics of this Special Issue include but are not limited to:

* Question answering: open-domain Q&A, knowledge-based Q&A...
* Knowledge extraction: Relation extraction, fine-grained entity recognition... * Text generation: summarization, style transfer, dial...
* Text classification: Sentiment/emotion analysis, semi-supervised and zero-shot learning...
* Behaviour modelling: early risk detection, cyberbullying, customer modelling...
* Dialogue systems: chatbots, voice assistants...
* Reinforcement learning
* Data augmentation
* Graph based approaches
* Adversarial approaches
* Multi-modal approaches
* Multi-lingual/cross-lingual approaches

More information at https://www.mdpi.com/journal/applsci/special_issues/Language_Processing

**** Co-editors

Prof. Dr. Arturo Montejo-Ráez
Guest Editor
SINAI Research Group, CEATIC, Universidad de Jaén, 23071 Jaén, Spain

Dr. Salud María Jiménez-Zafra
Guest Editor
SINAI Research Group, CEATIC, Universidad de Jaén, 23071 Jaén, Spain

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