We propose a way of extracting high-confidence association rules from datasets consisting of unlabeled trees. The antecedents are obtained through a computation akin to a hypergrap...
In this paper we propose a novel spatial associative classifier method based on a multi-relational approach that takes spatial relations into account. Classification is driven by s...
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...
Abstract. A new algorithm is presented for finding genotype-phenotype association rules from data related to complex diseases. The algorithm was based on Genetic Algorithms, a tech...
Vanessa Aguiar, Jose A. Seoane, Ana Freire, Cristi...
Many data mining tasks (e.g., Association Rules, Sequential Patterns) use complex pointer-based data structures (e.g., hash trees) that typically suffer from sub-optimal data loca...
Srinivasan Parthasarathy, Mohammed Javeed Zaki, We...