Abstract The application of data mining algorithms needs a goal-oriented preprocessing of the data. In practical applications the preprocessing task is very time consuming and has ...
Abstract In this paper we propose a novel parallel algorithm for frequent itemset mining. The algorithm is based on the filter-stream programming model, in which the frequent item...
Adriano Veloso, Wagner Meira Jr., Renato Ferreira,...
We presenthere an approachand algorithm for mining generalizedterm associations.The problem is to find co-occurrencefrequenciesof terms, given a collection of documents eachwith r...
Jonghyun Kahng, Wen-Hsiang Kevin Liao, Dennis McLe...
A hypergraph is a generalization of the traditional graph in which the edges are arbitrary non-empty subsets of the vertex set. It has been applied successfully to capture highord...
Constrained clustering has been well-studied for algorithms like K-means and hierarchical agglomerative clustering. However, how to encode constraints into spectral clustering rem...