We propose an unsupervised approach to learn associations between continuous-valued attributes from different modalities. These associations are used to construct a multi-modal t...
This paper investigates a brute-force technique for mining classification rules from large data sets. We employ an association rule miner enhanced with new pruning strategies to c...
Abstract. This paper proposes a novel approach named AGM to eciently mine the association rules among the frequently appearing substructures in a given graph data set. A graph tran...
We present a novel approach for classifying documents that combines different pieces of evidence (e.g., textual features of documents, links, and citations) transparently, through...
Adriano Veloso, Wagner Meira Jr., Marco Cristo, Ma...
Data mining extracts implicit, previously unknown and potentially useful information from databases. Many approaches have been proposed to extract information, and one of the most ...