In this paper, we investigate a new approach for literature mining. We use frequent subgraph mining, and its generalization topological structure mining, for finding interesting re...
Fan Wang, Ruoming Jin, Gagan Agrawal, Helen Piontk...
Background: Biomedical and chemical databases are large and rapidly growing in size. Graphs naturally model such kinds of data. To fully exploit the wealth of information in these...
Mining graph data is an active research area. Several data mining methods and algorithms have been proposed to identify structures from graphs; still, the evaluation of those resu...
The single minimum support (minsup) based frequent pattern mining approaches like Apriori and FP-growth suffer from“rare item problem”while extracting frequent patterns. That...
The application of frequent patterns in classification appeared in sporadic studies and achieved initial success in the classification of relational data, text documents and graph...