From its very beginning, the potential of extracting valuable knowledge from the Web has
been quite evident. Web mining, ie the application of data mining techniques to extract …

Privacy considerations often constrain data mining projects. This paper addresses the
problem of association rule mining where transactions are distributed across sources. Each …

Privacy preserving mining of distributed data has numerous applications. Each application
poses different constraints: What is meant by privacy, what are the desired results, how is the …

There has been concern over the apparent conflict between privacy and data mining. There
is no inherent conflict, as most types of data mining produce summary results that do not …

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

There exist emerging applications of data streams that have mining requirements. Although
single data stream mining has been extensively studied, little research has been done for …

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 …

Over the past two decades, business volume of hardware and software in the US has
decreased by about seventy percent, while the cost of management and support has grown …

(57) ABSTRACT A data processing system generates recommendations for on-line
shopping by scoring recommendations matching the customer's cart contents using by …

The goal of data mining is to extract or “mine” knowledge from large amounts of data.
However, data is often collected by several different sites. Privacy, legal and commercial …