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...
Time series pattern mining (TSPM) finds correlations or dependencies in same series or in multiple time series. When the numerous instances of multiple time series data are associ...
Discovering sequential patterns is an important problem for many applications. Existing algorithms find qualitative sequential patterns in the sense that only items are included ...
Chulyun Kim, Jong-Hwa Lim, Raymond T. Ng, Kyuseok ...
Recent research in mining user access patterns for predicting Web page requests focuses only on consecutive sequential Web page accesses, i.e., pages which are accessed by followi...
We develop an efficient algorithm for detecting frequent patterns that occur in sequence databases under certain constraints. By combining the use of bit vector representations of ...