Frequent itemset mining is a classic problem in data mining. It is a non-supervised process which concerns in finding frequent patterns (or itemsets) hidden in large volumes of d...
Adriano Veloso, Wagner Meira Jr., Srinivasan Parth...
Background: The development, in the last decade, of stochastic heuristics implemented in robust application softwares has made large phylogeny inference a key step in most compara...
In this paper, we show how the proposed model in ITU-T Recommendation G.1070 “Opinion model for video-telephony applications” cannot model properly the perceptual video qualit...
Topic models provide a powerful tool for analyzing large text collections by representing high dimensional data in a low dimensional subspace. Fitting a topic model given a set of...
Applications in Computer Networks often require high throughput access to large data structures for lookup and classification. Many advanced algorithms exist to speed these searc...