Performing data mining tasks in streaming data is considered a challenging research direction, due to the continuous data evolution. In this work, we focus on the problem of clust...
Maria Kontaki, Apostolos N. Papadopoulos, Yannis M...
When distributing 3D contents real-time over a network with a narrow bandwidth such as a telephone line, methods for streaming and data compression can be considered indispensable...
Toshiki Hijiri, Kazuhiro Nishitani, Tim Cornish, T...
The co-association (CA) matrix was previously introduced to combine multiple partitions. In this paper, we analyze the CA matrix, and address its difference from the similarity ma...
Learning from data streams is a research area of increasing importance. Nowadays, several stream learning algorithms have been developed. Most of them learn decision models that c...
In recent years, emerging applications introduced new constraints for data mining methods. These constraints are typical of a new kind of data: the data streams. In data stream pro...