Maguelonne Teisseire

Maguelonne Teisseire received a PhD in computing science from the Méditerranée University, France (1994). Her research interests focused on behavioral modeling and design. She is currently an assistant professor of computer science and engineering in Montpellier II University and Polytech’Montpellier, France. She is head of the Data Mining Group at the LIRMM Laboratory, Montpellier. Her interests focus on advanced data mining approaches when considering that data are time ordered. Particularly, she is interested in text mining and sequential patterns. Her research takes part on different projects supported by either National Government (RNTL) or regional projects. She has published numerous papers in refereed journals and conferences either on behavioral modeling or data mining.

Publications

Sequential Pattern Mining
Sequential Pattern Mining
Florent Masseglia, Maguelonne Teisseire, Pascal Poncelet. © 2009. 6 pages.
Sequential pattern mining deals with data represented as sequences (a sequence contains sorted sets of items). Compared to the association rule problem, a study of such data...
Peer-to-Peer Usage Analysis
Peer-to-Peer Usage Analysis
Florent Masseglia, Pascal Poncelet, Maguelonne Teisseire. © 2009. 6 pages.
With the huge number of information sources available on the Internet and the high dynamics of their data, peer-to-peer (P2P) systems propose a communication model in which each...
Data Mining Patterns: New Methods and Applications
Data Mining Patterns: New Methods and Applications
Pascal Poncelet, Florent Masseglia, Maguelonne Teisseire. © 2008. 324 pages.
Since the introduction of the Apriori algorithm a decade ago, the problem of mining patterns is becoming a very active research area, and efficient techniques have been widely...
Successes and New Directions in Data Mining
Successes and New Directions in Data Mining
Pascal Poncelet, Florent Masseglia, Maguelonne Teisseire. © 2008. 386 pages.
The problem of mining patterns is becoming a very active research area and efficient techniques have been widely applied to problems in industry, government, and science. From...
Sequential Pattern Mining
Sequential Pattern Mining
Florent Masseglia, Maguelonne Teisseire, Pascal Poncelet. © 2005. 5 pages.
Sequential pattern mining deals with data represented as sequences (a sequence contains sorted sets of items). Compared to the association rule problem, a study of such data...