Salvatore Stolfo, Andreas L. Prodromidis, Shelley Tselepis, Wenke Lee, Wei Fan, Philip K. Chan  Home/Search
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Abstract: In this paper, we describe the JAM system, a distributed, scalable and portable agent-based data mining system that employs a general approach to scaling data mining applications that we have come to call meta-learning. JAM provides a set of learning programs, implemented either as JAVA applets or applications, that compute models over data stored locally at a site. JAM also provides a set of meta-learning agents for combining multiple models that were learned (perhaps) at different sites. It... (Update)
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BibTeX entry: (Update)
S. J. Stolfo, A. L. Prodromidis, S. Tselepis, W. Lee, D. W. Fan, and P. K. Chan. Jam: Java agents for meta-learning over distributed databases. In Proceedings of the 3rd International Conference on Knowledge Discovery and Data Mining, pages 74--81, Newport Beach, CA, August 1997. AAAI Press. http://citeseer.ist.psu.edu/article/stolfo97jam.html More
@inproceedings{ stolfo97jam,
author = "Salvatore J. Stolfo and Andreas L. Prodromidis and Shelley Tselepis and Wenke Lee and Dave W. Fan and Philip K. Chan",
title = "{JAM}: Java Agents for Meta-Learning over Distributed Databases",
booktitle = "Knowledge Discovery and Data Mining",
pages = "74-81",
year = "1997",
url = "citeseer.ist.psu.edu/article/stolfo97jam.html" }
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