You are currently viewing a new version of our website. To view the old version click .

Advances in Artificial Intelligence Methods for Natural Language Processing

This special issue belongs to the section “Computing and Artificial Intelligence“.

Special Issue Information

Dear Colleagues,

Recent years have shown significant progress in natural language processing using methods related to artificial intelligence. This progress is made both in the construction of new algorithms, language representation, and data sets as well as more and more efficient hardware. 

The advances in the NLP domain have influences on information retrieval methods, dialogue systems, automatic categorization of large text repositories etc. Thus, the purpose of this Special Issue is to publish high-quality research papers as well as review articles addressing recent advances in the field of computational linguistics. We welcome works that relate to NLP, such as: machine translation, dialogue and chatbots, and summarization, natural language generation, and understanding.

Topics of Interest:

We are seeking papers on (but not limited to) the following general topics related to NLP:

  • Automatic categorization (classification and clustering) of the documents
  • Text representation
  • Language resources and tools   
  • Sentiment analysis
  • Effective algorithms for text processing (HPC 4 NLP)
  • Machine translation
  • Text summarization
  • Generation of natural language
  • Cognitive models of language understanding
  • Anti-plagiarism systems 
  • Word sense disambiguation
  • Information retrieval
  • Ontologies for natural language
  • Deep learning in NLP
  • Entity identification and linking

Prof. Dr. Julian Szymanski
Dr. Andrzej Sobecki
Prof. Dr. Higinio Mora
Prof. Dr. Doina Logofătu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Published Papers

Get Alerted

Add your email address to receive forthcoming issues of this journal.

XFacebookLinkedIn
Appl. Sci. - ISSN 2076-3417