Editorial of the special issue: Online fuzzy machine learning and data mining

Authors: Bouchachia, A., Lughofer, E. and Sanchez, D.

Journal: Information Sciences

Volume: 220

Pages: 1-4

ISSN: 0020-0255

DOI: 10.1016/j.ins.2012.10.005

Abstract:

The special issue of Information Sciences intends to investigate the relationship between fuzzy theory and ML/DM (machine learning and data mining). In the paper 'On-line dynamic adaptation of fuzzy preferences' by Marin, Isern, Moreno and Valls the authors propose an algorithm to extract information about users' preferences and to update it on-line as they perform searches on an information retrieval system. The paper 'Online Extraction of Main Linear Trends for Nonlinear Time-Varying Processes' by Kalhor, Araabi and Lucas deals with the problem of extracting the significant linear trends of a nonlinear time-varying process. Paper 'Online recognition of human activities and adaptation to habit changes by means of learning automata and fuzzy temporal windows' by Ros, Cuellar, Delgado and Vila introduces a method based on the concepts of learning automata and fuzzy temporal windows for human behavior recognition in a smart home.

Source: Scopus