Mining the knowledge mine: The hot spots methodology for mining large real world databases

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 1342, Issue , 1997, Pages 340-348

  Williams, Graham J ^a   Huang, Zhexue ^a  

^a CSIRO   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; DATABASE SYSTEMS; GOLD;

HOT SPOT; INTERACTIVE APPROACH; REAL-WORLD DATABASE; TRAINING SETS;

DATA MINING;

EID: 84961297619     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-63797-4_87     Document Type: Conference Paper

References (6)

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2. Huang, Z.: 1997, Clustering large data sets with mixed numeric and categorical values, in H. -J. Lu, H. Liu and H. Motoda (eds), Knowledge discovery and data mining: techniques and applications, World Scientific.
3. Mallows, C. and Pregibon, D.: 1996, The analysis of call-detail data, The Sydney International Statistical Congress.
4. Quinlan, J. R.: 1993, C4. 5: Programs for Machine Learning, Morgan Kaufmann, San Mateo, CA, 1993., Morgan Kaufmann, San Mateo, CA.
5. Viveros, M. S., Nearhos, J. P. and Rothman, M. J.: 1996, Applying data mining techniques to a health insurance information system, Proceedings of the 22nd VLDB Conference, Mumbai (Bombay), India, pp. 286-293.
6. Williams, G. J. and Huang, Z.: 1996, A case study in knowledge acquisition for insurance risk assessment using a kdd methodology, in P. Compton, R. Mi- zoguchi, H. Motoda and T. Menzies (eds), Pacific Knowledge Acquisition Workshop, pp. 117-129.