Toward ubiquitous mining of distributed data

The role of data-centric information is becoming increasingly important in our everyday professional and personal lives. The advent of laptops, palmtops, handhelds, and wearable computers is also making ubiquitous access to large quantity of data possible. Advanced analysis of distributed data for extracting useful knowledge is the next natural step in the world of ubiquitous computing. However, this will not come for free; it will introduce additional cost due to communication, computational, security among others. Distributed data mining techniques offer a technology to analyze distributed data by minimizing this cost to maintain the ubiquitous presence. This paper adopts the Collective Data Mining approach that offers a collection of different scalable and distributed data analysis techniques. It particularly focuses on two collective techniques for predictive data mining, presents some experimental results, and points the readers toward more extensive documentations of the technology.

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