Joint analysis of data from multiple sources has the potential to improve our understanding
of the underlying structures in complex data sets. For instance, in restaurant …

Advances in computing and communication over wired and wireless networks have resulted
in many pervasive distributed computing environments. The Internet, intranets, local area …

Many large organizations have multiple databases distributed in different branches, and
therefore multi-database mining is an important task for data mining. To reduce the search …

Multi-database mining is an important research area because (1) there is an urgent need for
analyzing data in different sources,(2) there are essential differences between mono-and …

We present a collective approach to learning a Bayesian network from distributed
heterogeneous data. In this approach, we first learn a local Bayesian network at each site …

Aggregation services play an important role in the domain of Wireless Sensor Networks
(WSNs) because they significantly reduce the number of required data transmissions, and …

The Principal Component Analysis (PCA) is a data dimensionality reduction tech-nique well-
suited for processing data from sensor networks. It can be applied to tasks like compression …

Advancements in computer and communication technologies demand new perceptions of
distributed computing environments and development of distributed data sources for storing …

Many organizations have an urgent need of mining their multiple databases inherently
distributed in branches (distributed data). In particular, as the Web is rapidly becoming an …

Photonics physically promises high-speed and low-consumption computing of matrix
multiplication. Nevertheless, conventional approaches are challenging to achieve large …