Data streams are often locally correlated, with a subset of streams exhibiting coherent patterns over a subset of time points. Subspace clustering can discover clusters of objects...
Mining sequential patterns in large databases is an important research topic. The main challenge of mining sequential patterns is the high processing cost due to the large amount ...
The conflict between resource consumption and query performance in the data mining context often has no satisfactory solution. This not only stands in sharp contrast to the need of...
Matthias Gimbel, Michael Klein, Peter C. Lockemann
Sequential pattern mining first proposed by Agrawal and Srikant has received intensive research due to its wide range applicability in many real-life domains. Various improvements...
Many real life sequence databases, such as customer shopping sequences, medical treatment sequences, etc., grow incrementally. It is undesirable to mine sequential patterns from s...