|Office||4126 Wean Hall|
Professor Faloutsos focuses on two major research areas: query by content in multi-media databases and data mining. The first area examines fast methods for approximate matching in multimedia databases. Typical queries are as follows: "in a collection of product photographs, find products that look like tennis shoes;" "in a collection of medical X-rays, find ones that look like the X-ray of the current patient, and list the corresponding diagnoses." Professor Faloutsos' group uses database methods, like 'R-trees,' to search for them efficiently.
The goal in data mining is to discover correlations ('rules') in a collection of records. For example, in a set of patient records with demographic characteristics, symptoms and diagnoses, the research group would like to find all the 'interesting' rules (e.g., 'patients > 50 years old with cholesterol > 300 have a 10 percent probability of heart attack'). The focus is on scalable algorithms for massive datasets, 'Active Disks,' and on lossy compression, which is closely related to data mining.