Abstract-- Data uncertainty is common in real-world applications due to various causes, including imprecise measurement, network latency, outdated sources and sampling errors. Thes...
Abstract. Data mining algorithms such as the Apriori method for finding frequent sets in sparse binary data can be used for efficient computation of a large number of summaries fr...
Abstract- Data streams of real numbers are generated naturally in many applications. The technology of online subsequence searching in data streams becomes more and more important ...
In this paper, we discuss Conceptual Knowledge Discovery in Databases (CKDD) in its connection with Data Analysis. Our approach is based on Formal Concept Analysis, a mathematical ...
Joachim Hereth Correia, Gerd Stumme, Rudolf Wille,...
Clustering, in data mining, is useful for discovering groups and identifying interesting distributions in the underlying data. Traditional clustering algorithms either favor clust...