Clustering methods for data-mining problems must be extremely scalable. In addition, several data mining applications demand that the clusters obtained be balanced, i.e., be of ap...
Frequent constraint violations on the data stored in a database may suggest that the semantics of the represented reality is changing. In this work we propose a methodology and a t...
We explore the automatic generation of test data that respect constraints expressed in the Object-Role Modeling (ORM) language. ORM is a popular conceptual modeling language, prim...
Yannis Smaragdakis, Christoph Csallner, Ranjith Su...
This paper proposes a prediction approach that combines grey prediction model with three-layer computing architecture in Web environment. It presents a refined prediction formula ...
We introduce a robust and efficient framework called CLUMP (CLustering Using Multiple Prototypes) for unsupervised discovery of structure in data. CLUMP relies on finding multip...