ISSA is a system integrating different structural mining tasks (only the sequential case, for the moment) by using a common unifying framework: a Galois lattice adapted to sequential data. After characterizing the Galois lattice, it is possible to compute either partial orders, or frequent sequential patterns, or also a new notion of association rules with order by just traversing its nodes. Our aim is to provide a visual tool based on a sound theory that can be useful in different contexts of analysis of structures.
ISSA Web page
ADATREENAT: Adaptive Closed Frequent Tree Mining
This software contains three closed tree mining algorithms: an incremental one IncTreeNat, a sliding-window based one, WinTreeNat, and finally one that mines closed trees adaptively from data streams, AdaTreeNat.
Closed patterns are powerful representatives of frequent patterns, since they eliminate redundant information. We propose a new approach for mining closed unlabeled rooted trees adaptively from data streams that change over time. Our approach is based on an effcient representation of trees and a low complexity notion of relaxed closed trees, and leads to an on-line strategy and an adaptive sliding window technique for dealing with changes over time.