SLIE 2021 : Semantic, Logics, Information Extraction and AI

Today, people working in Natural Language Processing (NLP) domain, especially Semantic, Logics and Information Extraction (SLIE), are often members of interdisciplinary teams, including computer scientists, experts in artificial intelligence, mathematicians, statisticians, logicians, linguists, philosophers, cognitive scientists, cognitive psychologists, psycholinguists, anthropologists and neuroscientists, among others. NLP-SLIE is not just a subfield of computer science, information engineering, and artificial intelligence. It is, also, connected to cognitive sciences through the development of cognitive theories. We can see NLP-SLIE divided into two parts: (1) its theoretical descriptions; (2) its concrete implementations. The theoretical aspect includes philosophical hypothesis, psychological hypothesis, linguistics methods as semantics, syntax, morphology, etc., or numerical methods as classification, neural networks, Naive Bayes, deep learning, etc. At the present stage of research, there still a gap between theoretical approaches and computer implementations. There are many computer applications without any solid theoretical foundations, and there are many theoretical methods with no computer implementation. Theoretical Methods and computational implementations for the NLP-SLIE must take into account this epistemological chain for to lead to effective, robust and reliable systems.