Toward ubiquitous mining of distributed data

Rajeev Ayyagari, Byung Hoon Park, Daryl Hershberger, Hillol Kargupta

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
Pages (from-to)138-148
Number of pages11
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume4384
DOIs
StatePublished - 2001
Externally publishedYes

Fingerprint

Dive into the research topics of 'Toward ubiquitous mining of distributed data'. Together they form a unique fingerprint.

Cite this