Data mining on large data warehouses is becoming increasingly important. In support of this trend, we consider a spectrum of architectural alternatives for coupling mining with da...
Emerging applications introduce the requirement for novel association-rule mining algorithms that will be scalable not only with respect to the number of records (number of rows) ...
Alexandros Nanopoulos, Apostolos N. Papadopoulos, ...
Existing association rule mining algorithms suffer from many problems when mining massive transactional datasets. Some of these major problems are: (1) the repetitive I/O disk sca...
In this paper, we first focus our attention on the question of how much space remains for performance improvement over current association rule mining algorithms. Our strategy is...
We present a general Multi-Agent System framework for distributed data mining based on a Peer-toPeer model. The framework adopts message-based asynchronous communication and a dyn...
In this paper, a new pattern-growth algorithm is presented to mine frequent sequential patterns using First-Occurrence Forests (FOF). This algorithm uses a simple list of pointers...
Abstract. We present a method for mining frequently occurring objects and scenes from videos. Object candidates are detected by finding recurring spatial arrangements of affine cov...
Data privacy is a major concern that threatens the widespread deployment of Data Grids in domains such as health-care and finance. We propose a unique approach for obtaining knowl...
In this paper, we investigate and utilize the characteristic of the group movement of objects to achieve energy conservation in the inherently resource-constrained wireless object ...
The process of resource distribution and load balance of a distributed P2P network can be described as the process of mining Supplement Frequent Patterns (SFPs) from query transact...
Yintian Liu, Yingming Liu, Tao Zeng, Kaikuo Xu, Ro...