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

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

Journal: Inf. Sci.

Volume: 220

Pages: 1-4

DOI: 10.1016/j.ins.2012.10.005

This data was imported from Scopus:

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

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.

This source preferred by Hamid Bouchachia

This data was imported from Web of Science (Lite):

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

Journal: INFORMATION SCIENCES

Volume: 220

Pages: 1-4

eISSN: 1872-6291

ISSN: 0020-0255

DOI: 10.1016/j.ins.2012.10.005

The data on this page was last updated at 04:40 on November 19, 2017.