Adaptive algorithm based on clustering techniques for custom reading plans
Marylin Giugni, Francisca Grimón, Luis Álvarez, Joaquín del Río Fernández, José María Monguet Fierro · Computational intelligence · 2010
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-a-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.