Title: A formal theoretical framework for a flexible classification process
Authors: Ismaïl Biskri; Mohamed Hassani
Addresses: Laboratoire de Mathématiques et Informatique Appliquées, Université du Québec à Trois-Rivières, CP 500, Trois-Rivières, Québec, Canada ' Laboratoire de Mathématiques et Informatique Appliquées, Université du Québec à Trois-Rivières, CP 500, Trois-Rivières, Québec, Canada
Abstract: The classification process is a complex technique that connects language, text, information and knowledge theories with computational formalisation, statistical and symbolic approaches, standard and non-standard logics, etc. This process should always be under the control of the user according to his subjectivity, his knowledge and the purpose of his analysis. It becomes important to create platforms to support the design of classification tools, their management, and their adaptation to new needs and experiments. In the last years, several platforms for data digging including textual data where classification is the main functionality have emerged. However, they lack flexibility and formal foundations. We propose in this paper a formal model with strong logical foundations based on applicative type systems.
Keywords: classification; flexibility; applicative systems; operators/operands; combinatory logics; inferential calculus; compositionality; processing chains; modules; discovery process; collaborative intelligent science.
International Journal of Data Mining, Modelling and Management, 2021 Vol.13 No.1/2, pp.17 - 36
Received: 13 Aug 2018
Accepted: 07 Mar 2019
Published online: 09 Feb 2021 *