1. Agarwal, R., Imielinski, T., & Swami, A. (1993). Mining association rules between sets of items in large databases. In Proceedings of the ACM SIGMOD international conference on management of data, Washington DC, USA (pp. 1–22).
2. Agarwal, R., & Srikant, R. (2005). Mining sequential patterns. In Proceedings of the eleventh international conference on data engineering, Taipei, Taiwan (pp. 3–14).
3. Alcalá, J., Sánchez, L., García, S., del Jesús, M. J., Ventura, S., Garrell, J. M., et al. (in press). KEEL: A data mining software tool for assessing the performance of knowledge extraction-based on evolutionary algorithms. Soft computing: A fusion of foundations, methodologies and applications.
4. Anozie, N., & Junker, B. W. (2006). Predicting end-of-year accountability assessment scores from monthly student records in an online tutoring system. In Educational data mining AAAI workshop, California, USA (pp. 1–6).
5. Arroyo, I., Murray, T., Woolf, B., & Beal, C. (2004). Inferring unobservable learning ariables from students’ help seeking behavior. In Intelligent tutoring systems, Alagoas, Brazil (pp. 782–784).