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Special Issue "Advances in Computational Linguistics"
Deadline for manuscript submissions: 15 January 2020.
Interests: multiagent systems; ontologies; knowledge representation; computational linguistics
Interests: ontologies; knowledge representation; computational linguistics; cognitive linguistics
Since the emergence of the digital computer, the processing of information encoded in natural language has been one of the goals pursued by researchers in the field. This is because, due to the flexibility and expressiveness of human language, communication between man and machine and the extraction of information would get huge leverage. However, because of the polysemic and pragmatic nature of natural language, this goal has always been hard to achieve and was somewhat abandoned during the 1980s and 1990s.
Increasing computational power; the shift in approach from a symbolic approach to a statistical approach; and, more recently, the emergence of deep learning have enabled that goal to be achieved once more. As a result, research institutions and large technology companies have again invested heavily in research on natural language processing. Today, it is possible to acquire home computing devices that interact through natural language and can control household appliances, play music, and perform other tasks. Nonetheless, there is still much room for progress, and there are obstacles to be overcome. The treatment of metaphors and other figures of language, the generation of poetic texts, the generation of paraphrases and semantic similarity, and systems of questions and answers are some of the challenges, just to name a few.
The aim of this Special Issue is to present research dedicated to producing advances in challenging areas of natural language processing, both oral and written.
Topics of interest include but are not limited to the following:
- Generating text poems and lyrics;
- Generation of paraphrase and semantic similarity;
- Contextual question and answer systems;
- Fake News detection;
- Word-level and sentence-level semantics;
- Sentiment analysis and argument mining;
- Textual inference;
- Discourse and pragmatics;
- Methodologies and tools for corpus annotation.
Dr. Alcione de Paiva Oliveira
Dr. Alexandra Moreira
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. Information is an international peer-reviewed open access monthly 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 1000 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
- Computational linguistics
- Sentiment analysis
- Dialogue and interactive systems
- Discourse and pragmatics
- Document analysis
- Natural language generation
- Natural language semantics
- Information extraction
- Text mining
- Machine learning
- Machine translation
- Question answering
- Natural language resources
- Textual inference
The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.
Title: Computational Linguistics: from formal systems to deep learning
Authors: Alexandra Moreira, Maurílio Possi, Alcione de Paiva Oliveira
Abstract: Computational linguistics, which aims to make computational devices able to interact through and process natural human language, was born almost simultaneously with the emergence of electronic computing. However, its evolution has gone through several moments, some of great enthusiasm and optimism, others of frustration and discouragement. Several techniques and approaches have been tried, from the use of formal systems with well-defined semantics and grammar needs, through complex statistical systems to sophisticated deep neural network architectures such as long short term memory and recent transformers. In each of these phases advances were made and the knowledge gained served as the basis for subsequent achievements. However, recent advances in hardware, the representation of textual elements in large vectors and neural network architectures have led the area to experience a sequence of highly successful and impactful cases. Recent achievements have turn it in a dynamic research area and an important field for application development that is being explored by leading technology companies. There are several devices on the market, which can be purchased at a relatively low cost, which allow the user to interact through natural language to obtain information such as weather, the name of the singer of a particular song; to control Home appliances by allowing it to turn on the air conditioner or turn off a light; or to perform an action such as acquiring a good or playing a song. Nonetheless, many advances have yet to be made in order to allow humans to be able to interact with computational devices through natural language in the same way that humans interact with native speakers of the same language. How to make computers understand or create new metaphors, metonymies or other figures of language? Is it possible to develop natural language systems capable of producing lyrics or poetry on the same level as humans? Can we produce systems capable of assigning new meanings to syntactic elements that are immediately perceived as coherent by humans? In this paper we account on the evolution of computational linguistics, drawing a parallel with the evolution of linguistic theories and speculating on the possibilities of evolution of the area and its possible limitations.