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A general probabilistic framework for clustering individuals and objects
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Source Conference on Knowledge Discovery in Data archive
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining table of contents
Boston, Massachusetts, United States
Pages: 140 - 149  
Year of Publication: 2000
ISBN:1-58113-233-6
Authors
Igor V. Cadez  Department of Information and Computer Science, University of California, Irvine, Irvine, CA
Scott Gaffney  Department of Information and Computer Science, University of California, Irvine, Irvine, CA
Padhraic Smyth  Department of Information and Computer Science, University of California, Irvine, Irvine, CA
Sponsors
SIGKDD: ACM Special Interest Group on Knowledge Discovery in Data
AAAI : Am Assoc for Artifical Intelligence
SIGART: ACM Special Interest Group on Artificial Intelligence
SIGMOD: ACM Special Interest Group on Management of Data
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 4,   Downloads (12 Months): 46,   Citation Count: 13
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REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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CITED BY  13
 
 
 
 
 
 
 

Collaborative Colleagues:
Igor V. Cadez: colleagues
Scott Gaffney: colleagues
Padhraic Smyth: colleagues

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