Data mining

Data mining is data analysis + algorithmics. The objective is to develop methods to efficiently extract useful information from large data sets. I have made contributions to the analytical foundations of this field, as well as to applications within medicine and personalized information systems. Please note that I take great care to safeguard any private personal information that is needed in my work.

My earlier work in data mining with colleagues and students at WPI focused on the paradigm of association rules (e.g., Lin*, W.-Y., Alvarez, S. A., Ruiz, C., "Efficient Adaptive-Support Association Rule Mining for Recommender Systems", Data Mining and Knowledge Discovery, Vol. 6, No. 1, pp. 83-105, Jan. 2002). I have also collaborated with medical colleagues from the U. of Massachusetts Medical School. My more recent work involves the discovery of statistically significant patterns in data arising in human sleep studies and in surgical oncology, using probabilistic clustering techniques.

Selected papers on data mining (asterisks * denote student co-authors)