In multi-database mining, there can be many local patterns (frequent itemsets or association rules) in each database. At the end of multi-database mining, it is necessary to analyz...
Chengqi Zhang, Meiling Liu, Wenlong Nie, Shichao Z...
—An efficient algorithm for mining important association rule from multi-relational database using distributed mining ideas. Most existing data mining approaches look for rules i...
—In this paper, we explore a new data mining capability that involves mining path traversal patterns in a distributed information-providing environment where documents or objects...
The goal of graph clustering is to partition objects in a graph database into different clusters based on various criteria such as vertex connectivity, neighborhood similarity or t...
Discovery of sequential patterns is an essential data mining task with broad applications. Among several variations of sequential patterns, closed sequential pattern is the most u...