— Distributed data mining has recently caught a lot of attention as there are many cases where pooling distributed data for mining is probibited, due to either huge data volume o...
Chak-Man Lam, Xiaofeng Zhang, William Kwok-Wai Che...
Correlated or discriminative pattern mining is concerned with finding the highest scoring patterns w.r.t. a correlation measure (such as information gain). By reinterpreting corre...
In recent years there has been an increased interest in frequent pattern discovery in large databases of graph structured objects. While the frequent connected subgraph mining pro...
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...
GRD is an algorithm for k-most interesting rule discovery. In contrast to association rule discovery, GRD does not require the use of a minimum support constraint. Rather, the user...