Alicia Troncoso

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Evaluating in Massive Open Online Courses (MOOCs) is a difficult task because of the huge number of students involved in the courses. Peer grading is an effective method to cope with this problem, but something must be done to lessen the effect of the subjective evaluation. In this paper we present a matrix factorization approach able to learn from the(More)
Data mining has become an essential tool during the last decade to analyze large sets of data. The variety of techniques it includes and the successful results obtained in many application fields, make this family of approaches powerful and widely used. In particular, this work explores the application of these techniques to time series forecasting.(More)
  • Phani Krishna Kishore, Ashok Kumar Madamsetti, +18 authors David W. Cheung
  • 2014
Generating rules from quantitative data has been widely studied ever since Agarwal and Srikanth explored the problem through their works on association rule mining. Discretization of the ranges of the attributes has been one of the challenging tasks in quantitative association rule mining that guides the rules generated. Also several algorithms are being(More)
In this paper a hybrid metaheuristic for biclustering based on Scatter Search and Genetic Algorithms is presented. A general scheme of Scatter Search has been used to obtain high--quality biclusters, but a way of generating the initial population and a method of combination based on Genetic Algorithms have been chosen. Moreover, in the own algorithm the(More)
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