Data mining and knowledge discovery: making sense out of data

Current computing and storage technology is rapidly outstripping society's ability to make meaningful use of the torrent of available data. Without a concerted effort to develop knowledge discovery techniques, organizations stand to forfeit much of the value from the data they currently collect and store.

[1]  Richard O. Duda,et al.  Pattern classification and scene analysis , 1974, A Wiley-Interscience publication.

[2]  William Frawley,et al.  Knowledge Discovery in Databases , 1991 .

[3]  Umesh V. Vazirani,et al.  An Introduction to Computational Learning Theory , 1994 .

[4]  Gregory Piatetsky-Shapiro,et al.  Knowledge Discovery in Personal Data vs. Privacy: A mini-symposium , 1995, IEEE Expert.

[5]  Heikki Mannila,et al.  Fast Discovery of Association Rules , 1996, Advances in Knowledge Discovery and Data Mining.

[6]  Usama M. Fayyad,et al.  Automating the Analysis and Cataloging of Sky Surveys , 1996, Advances in Knowledge Discovery and Data Mining.

[7]  Daryl Pregibon,et al.  A Statistical Perspective on Knowledge Discovery in Databases , 1996, Advances in Knowledge Discovery and Data Mining.

[8]  Usama M. Fayyad,et al.  Automated cataloging and analysis of sky survey image databases: the SKICAT system , 1993, CIKM '93.

[9]  Padhraic Smyth,et al.  From Data Mining to Knowledge Discovery: An Overview , 1996, Advances in Knowledge Discovery and Data Mining.

[10]  Kevin T. Kelly,et al.  Discovering Causal Structure. , 1989 .

[11]  Belur V. Dasarathy,et al.  Nearest neighbor (NN) norms: NN pattern classification techniques , 1991 .

[12]  JoBea Way,et al.  The evolution of synthetic aperture radar systems and their progression to the EOS SAR , 1991, IEEE Trans. Geosci. Remote. Sens..

[13]  David Heckerman,et al.  Bayesian Networks for Knowledge Discovery , 1996, Advances in Knowledge Discovery and Data Mining.