Current outlier detection schemes typically output a numeric score representing the degree to which a given observation is an outlier. We argue that converting the scores into wel...
Given a large spatio-temporal database of events, where each event consists of the fields event ID, time, location, and event type, mining spatio-temporal sequential patterns ident...
Closed patterns are powerful representatives of frequent patterns, since they eliminate redundant information. We propose a new approach for mining closed unlabeled rooted trees a...
With the increasing availability of spatial data in many applications, spatial clustering and outlier detection has received a lot of attention in the database and data mining comm...
Real-time frequent pattern mining for business intelligence systems are currently in the focal area of research. In a number of areas of doing business, especially in the arena of...