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Issue title: Cognitive Informatics and Computational Intelligence: Theory and Applications
Article type: Research Article
Authors: Pal, Sankar K. | Banerjee, Romi | Dutta, Soumitra | Sarma, Samar Sen
Affiliations: Machine Intelligence Unit, Indian Statistical Institute, Kolkata 700 108, India. [email protected] | Center for Soft Computing Research, Indian Statistical Institute, Kolkata 700 108, India. [email protected] | INSEAD, Blvd de Constance, Fontainebleau 77305, France | Department of Computer Sc. and Engineering, University of Calcutta, Kolkata 700 009, India
Note: [] This project is being carried out under the guidance of Professor Sankar K. Pal, who is the Principal Investigator of the Center for Soft Computing Research and a J.C. Bose Fellow of the Government of India. Address for correspondence: Centre for Soft Computing Research, Indian Statistical Institute, 203 B. T. Road, Kolkata 700 108, India
Note: [] This project is being carried out under the guidance of Professor Sankar K. Pal, who is the Principal Investigator of the Center for Soft Computing Research and a J.C. Bose Fellow of the Government of India.
Abstract: The Z-number is a new fuzzy-theoretic concept, proposed by Zadeh in 2011. It extends the basic philosophy of Computing With Words (CWW) to include the perception of uncertainty of the information conveyed by a natural language statement. The Z-number thus, serves as a model of linguistic summarization of natural language statements, a technique to merge human-affective perspectives with CWW, and consequently can be envisaged to play a radical role in the domain of CWW-based system design and Natural Language Processing (NLP). This article presents a comprehensive investigation of the Z-number approach to CWW. We present here: a) an outline of our understanding of the generic architecture, algorithm and challenges underlying CWW in general; b) a detailed study of the Z-number methodology - where we propose an algorithm for CWW using Z-numbers, define a Z-number based operator for the evaluation of the level of requirement satisfaction, and describe simulation experiments of CWW utilizing Z-numbers; and c) analyse the strengths and the challenges of the Z-numbers, and suggest possible solution strategies. We believe that this article would inspire research on the need for inclusion of human-behavioural aspects into CWW, as well as the integration of CWW and NLP.
Keywords: Cognition, fuzzy sets, linguistics, machine learning, text-summarization, dialogue-based systems, affective computing, Natural Language Processing (NLP), perceptions, soft computing, natural computing
DOI: 10.3233/FI-2013-831
Journal: Fundamenta Informaticae, vol. 124, no. 1-2, pp. 197-229, 2013
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