A fundamental building block of many data mining and analysis approaches is density estimation as it provides a comprehensive statistical model of a data distribution. For that re...
We propose an In-Network Data-Centric Storage (INDCS) scheme for answering ad-hoc queries in sensor networks. Previously proposed In-Network Storage (INS) schemes suffered from St...
The rapid growth of transactional data brought, soon enough, into attention the need of its further exploitation. In this paper, we investigate the problem of securing sensitive k...
In this paper, we propose an approach for efficient approximative RkNN search in arbitrary metric spaces where the value of k is specified at query time. Our method uses an approx...
New optimization techniques, e. g., in data stream management systems (DSMSs), make the treatment of disjunctive predicates a necessity. In this paper, we introduce and compare me...
In this paper, we study the problem of learning block classification models to estimate block functions. We distinguish general models, which are learned across multiple sites, an...
The widespread use of templates on the Web is considered harmful for two main reasons. Not only do they compromise the relevance judgment of many web IR and web mining methods suc...
Karane Vieira, Altigran Soares da Silva, Nick Pint...
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...