Frequent embedded subtree pattern mining is an important data mining problem with broad applications. In this paper, we propose a novel embedded subtree mining algorithm, called Pr...
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...
In many application fields, huge binary datasets modeling real life-phenomena are daily produced. The dataset records are usually associated with observations of some events, and...
Sustained emerging spatio-temporal co-occurrence patterns (SECOPs) represent subsets of object-types that are increasingly located together in space and time. Discovering SECOPs i...
Mete Celik, Shashi Shekhar, James P. Rogers, James...
Remote sensing image databases are the fastest growing archives of spatial information. However, we still have a limited capacity for extracting information from large remote sens...
Marcelino Pereira dos Santos Silva, Gilberto C&aci...