Traditional Data Mining and Knowledge Discovery algorithms assume free access to data, either at a centralized location or in federated form. Increasingly, privacy and security co...
Abstract. The concept of similarity is fundamentally important in almost every scientific field. Clustering, distance-based outlier detection, classification, regression and sea...
We present a novel algorithm called Clicks, that finds clusters in categorical datasets based on a search for k-partite maximal cliques. Unlike previous methods, Clicks mines subs...
Mohammed Javeed Zaki, Markus Peters, Ira Assent, T...
In this paper we study when the disclosure of data mining results represents, per se, a threat to the anonymity of the individuals recorded in the analyzed database. The novelty o...
Maurizio Atzori, Francesco Bonchi, Fosca Giannotti...
We study the problem of mining frequent value sets from a large sensor network. We discuss how sensor stream data could be represented that facilitates efficient online mining and ...