This paper describes a method for the segmentation of dynamic data. It extends well known algorithms developed in the context of static clustering (e.g., the c-means algorithm, Ko...
This demonstration shows how semantic schema matching technology is being incorporated into the BEA AquaLogic Data Services Platform. Specifically, it demonstrates how the manuall...
Michael J. Carey, Shahram Ghandeharizadeh, K. Meht...
This paper presents a framework for a learning based approach to dynamically evolve the conceptual structure of a database in order to facilitate virtual representation of data in ...
Abstract. This paper proposes a general framework for classifying data streams by exploiting incremental clustering in order to dynamically build and update an ensemble of incremen...
Ioannis Katakis, Grigorios Tsoumakas, Ioannis P. V...
Large area mapping at high resolution underwater continues to be constrained by sensor-level environmental constraints and the mismatch between available navigation and sensor acc...
Hanumant Singh, Christopher N. Roman, Oscar Pizarr...