Data Mining Grand Challenges

Published by on May 28, 2004

Conference paper

Part of the Lecture Notes in Computer Science book series (LNAI,volume 3056)

PAKDD 2004: Advances in Knowledge Discovery and Data Mining pp 2


The past two decades has seen a huge wave of computational systems for the “digitization” of business operations from ERP, to manufacturing, to systems for customer interactions. These systems increased the throughput and efficiency of conducting “transactions” and resulted in an unprecedented build-up of data captured from these systems. The paradoxical reality that most organizations face today is that they have more data about every aspect of their operations and customers, yet they find themselves with an ever diminishing understanding of either. Data Mining has received much attention as a technology that can possibly bridge the gap between data and knowledge.

Author information

Authors and Affiliations

President, DMX Group, LLC, USA

Usama Fayyad

Editor information

Editors and Affiliations

School of Engineering and Information Technology, Deakin University, VIC 3125, Australia

Honghua Dai

University of Illinois at Urbana-Champaign, 61801, Urbana, IL, USA

Ramakrishnan Srikant

Faculty of Engineering and Information Technology, Centre for Quantum Computation and Intelligent Systems, and Australian ACS National Committee for Artificial Intelligence, University of Technology, Sydney, Australia

Chengqi Zhang

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