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Artificial Intelligence
Data Mining: Concepts, Models, Methods and Algorithms
Data Mining: Concepts, Models, Methods and Algorithms
A Fast Elitist Non-dominated Sorting Genetic Algorithm for Multi-objective Optimisation: NSGA-II
PPSN VI Proceedings of the 6th International Conference on Parallel Problem Solving from Nature
Web usage mining: discovery and applications of usage patterns from Web data
ACM SIGKDD Explorations Newsletter
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ICALT '05 Proceedings of the Fifth IEEE International Conference on Advanced Learning Technologies
Moodle E-Learning Course Development
Moodle E-Learning Course Development
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Educational data mining: A survey from 1995 to 2005
Expert Systems with Applications: An International Journal
JCLEC: a Java framework for evolutionary computation
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Special issue (pp 315-357) "Ordered structures in many-valued logic"
Towards personalized recommendation by two-step modified Apriori data mining algorithm
Expert Systems with Applications: An International Journal
Web Usage Mining to Evaluate the Transfer of Learning in a Web-Based Learning Environment
WKDD '08 Proceedings of the First International Workshop on Knowledge Discovery and Data Mining
Using genetic algorithms for data mining optimization in an educational web-based system
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
G3P-MI: A genetic programming algorithm for multiple instance learning
Information Sciences: an International Journal
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An innovative technique based on multi-objective grammar guided genetic programming (MOG3P-MI) is proposed to detect the most relevant activities that a student needs to pass a course based on features extracted from logged data in an education web-based system. A more flexible representation of the available information based on multiple instance learning is used to prevent the appearance of a great number of missing values. Experimental results with the most relevant proposals in multiple instance learning in recent years demonstrate that MOG3P-MI successfully improves accuracy by finding a balance between specificity and sensitivity values. Moreover, simple and clear classification rules which are markedly useful to identify the number, type and time of activities that a student should do within the web system to pass a course are provided by our proposal.