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...
We consider the problem of finding association rules that make nearly optimal binary segmentations of huge categorical databases. The optimality of segmentation is defined by an o...
Imbalanced data learning has recently begun to receive much attention from research and industrial communities as traditional machine learners no longer give satisfactory results. ...
We apply a well-known Bayesian probabilistic model to textual information retrieval: the classification of documents based on their relevance to a query. This model was previously...
It is generally believed that data mining results do not violate the anonymity of the individuals recorded in the source database. In fact, data mining models and patterns, in orde...
Maurizio Atzori, Francesco Bonchi, Fosca Giannotti...