Special Issue "Natural Language Processing: Emerging Neural Approaches and Applications"
Deadline for manuscript submissions: 31 July 2020.
Interests: artificial intelligence; natural language processing; decision support systems; cognitive systems; knowledge-based technologies
Special Issues and Collections in MDPI journals
Interests: artificial intelligence; natural language processing; cognitive systems; machine vision; cloud computing
Interests: knowledge-based technologies; natural language processing; decision support systems; dialog systems and chatbots
Interests: fuzzy modeling; system interpretability; classification; natural language processing; deep neural networks
Special Issues and Collections in MDPI journals
In recent years, Artificial Intelligence has led to impressive achievements on a variety of complex cognitive tasks, matching or even beating humans. In the field of natural language processing (NLP), the use of deep learning models in the last five years has allowed AI to surpass human levels on many important tasks, such as machine translation and machine reading comprehension, and reach considerable improvements in other real-world NLP applications, such as image captioning, visual question answering and conversational systems, search and information retrieval, sentiment analysis, and recommender systems.
Despite the remarkable success of deep learning in different NLP tasks, significant challenges yet remain that make natural language development and understanding among the least understood human capabilities from a cognitive perspective. Indeed, the current deep learning methods have been scaled up and improved, but, as a side effect, their complexity has grown, assuming the form of empirical engineering solutions. Moreover, they have assumed the characteristic of being extremely data-hungry and are not applicable to languages with scarce or zero datasets. Furthermore, they are not able to explain their outputs, which is relevant for using and improving natural language systems. Summarizing, current deep learning systems do not provide a human-like computational model of cognition that is able to acquire, comprehend, and generate natural language as well as ground it and perform common-sense reasoning on physical concepts, objects, and events of the external world.
This Special Issue is intended to provide an overview of the research being carried out in the area of natural language processing to face these open issues, with a particular focus on both emerging approaches for language learning, understanding, production, and grounding, interactively or autonomously from data, in cognitive and neural systems, as well as on their potential or real applications in different domains. To this end, the Special Issue aims to gather researchers with a broad expertise in various fields—natural language processing, cognitive science and psychology, Artificial Intelligence and neural networks, computational modeling and neuroscience—to discuss their cutting-edge work as well as perspectives on future directions in this exciting field. Original contributions are sought, covering the whole range of theoretical and practical aspects, technologies, and systems in this research area.
The topics of interest for this Special Issue include but are not limited to:
- Natural language understanding, generation, and grounding;
- Multilingual and cross-lingual distributional representations and universal language models;
- Conversational systems/interfaces and question answering;
- Sentiment analysis, emotion detection, and opinion mining;
- Document analysis, information extraction, and text mining;
- Machine translation;
- Search and information retrieval;
- Common-sense reasoning;
- Computer/human interactive learning;
- Neuroscience-inspired cognitive architectures;
- Trustworthy and explainable artificial intelligence;
- Cognitive and social robotics;
- Applications in science, engineering, medicine, healthcare, finance, business, law, education, transportation, retailing, telecommunication, and multimedia.
Dr. Massimo Esposito
Dr. Giovanni Luca Masala
Dr. Aniello Minutolo
Dr. Marco Pota
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 papers will be 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 100 words) can be sent to the Editorial Office for announcement on this website.
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 1800 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.
- Natural language processing
- Text analytics
- Interactive and reinforcement learning
- Machine/deep learning
- Transfer learning
- Cognitive systems