Main Conference: International Semantic Intelligence Conference

(ISIC 2022)

Georgia Southern University (Armstrong Campus), Savannah, United States

https://www.ifis.uni-luebeck.de/~groppe/isic/

Computational Intelligence (CI) includes approaches and methods which consist of theories, theorems, proofs, axioms, applications and comparisons of computationally motivated paradigms. It provides computational solutions of multi-domain problems and applications which deals with the datasets ranging from database to exascale, homogeneity to heterogeneity, volume to velocity, variety to veracity. In today's era, when Exabytes of data is being generated on a daily basis, there is a great need of some intelligent methods and tools that would be robust and compatible to analyse and extract the meaningful information from them and help the users in making some fruitful and quick decisions. In view of these factors CI, its concepts, applications and meta-heuristics find great applications in solving real life problems. The aim of this workshop is to record and disseminate the contributions from researchers, academicians and industry experts in the CI domain. This workshop is a correct platform for information exchange and to bring about quantifiable change to the scientific output.

Natural language has semantics, pragmatics for the people communicating in a particular language to express their sentiments, feelings, behaviour. Human brain is a marvellous machine which can translate and understand the text/audio in natural language. In order to design an application to make a computer understand the natural language and interpret the way humans do, is the primary task of any natural language processing system. Natural language processing is a wide area with multi-facets applications in various domains. Natural language processing is ubiquitous and is likely to see a more powerful and useful future. Some of the unknowing use of natural language processing tools in our day-to-day life are- predictive typing, autocorrect, spell checker, grammar checker, duplicate detection, spam detection and so on.

Semantic representations at different levels – word, sentence, paragraph – are central to many solutions to Natural Language Processing (NLP) tasks. Text annotation, information retrieval, sentiment analysis, text summarization, question answering, and machine translation solutions have achieved significant improvements using semantic representations of words. The number of tasks has also grown with the popularization of unsupervised word embeddings, a fast and efficient way of estimating continuous representations of words. Now, representations derived from deep learning methods are giving a new boost to the field.

The proposed special issue can become a good platform for information exchange to bring quantifiable change to the scientific output of natural language processing system. Systems thus developed using NLP can be used for the welfare of society and mankind.