Adaptive algorithm based on clustering techniques for custom reading plans

Authors:
Marylin Giugni;Francisca Grimón;Luis León;Joaquín Fernández;Joseph Monguet
Affiliations:
Faculty of Science and Technology, University of Carabobo, Valencia, Venezuela;Faculty of Science and Technology, University of Carabobo, Valencia, Venezuela;Faculty of Science and Technology, University of Carabobo, Valencia, Venezuela;Multimedia Applications Laboratory, Polytechnic University of Catalunya, Spain;Multimedia Applications Laboratory, Polytechnic University of Catalunya, Spain
Venue:
CIMMACS '10 Proceedings of the 9th WSEAS international conference on computational intelligence, man-machine systems and cybernetics
Year:
2010

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Abstract

Individuals use Information and Communication Technologies (ICT) to relate remotely to each other, perform any sort of transactions, and produce and assimilate large volumes of information, among other things. This has led information repositories in digital format to grow exponentially. At the same time, accessing large volumes of information and selecting the closest one to the user's interests is increasingly difficult. With the aim of facing this problem, a tool oriented toward the personalization of readings plans in a learning environment, was developed with a view to assessing its effectiveness and the user's satisfaction vis-à-vis the proposed adaptation algorithm. This application is based on information recovery techniques, clustering algorithms and adaptation rules to adjust the user's model to contents and objects of study. The initial results reflect the effectiveness of the system and the users' acceptance degree.