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...
We describe an efficient framework for Web personalization based on sequential and non-sequential pattern discovery from usage data. Our experimental results performed on real us...
Bamshad Mobasher, Honghua Dai, Tao Luo, Miki Nakag...
The problem of mining spatiotemporal patterns is finding sequences of events that occur frequently in spatiotemporal datasets. Spatiotemporal datasets store the evolution of object...
Abstract. Solving inductive queries which have to return complete collections of patterns satisfying a given predicate has been studied extensively the last few years. The specific...
In this paper, we present a novel frequent generalized pattern mining algorithm, called GP-Close, for mining generalized associations from RDF metadata. To solve the overgeneraliz...