(Enter summary)
Abstract: Agent-Based Knowledge Discovery provides a new
technique for performing data-mining over distributed
databases. By combining techniques from Distributed AI
and Machine Learning, software agents equipped with
learning algorithms mine local databases. These agents
then co-operate to integrate the knowledge obtained, before
presenting the results to the user. We are currently
exploring the use of a new software agent language, AgentK
and the application of first order learning techniques to... (Update)
Context of citations to this paper: More
.... of this approach are the meta learning systems proposed by Chan and Stolfo (1996) and the agent based approach advocated by Davies and Edwards (1995) . Meta learning decomposes the initial training set into n subsets. Each of these is then used to train a classifier. The...
...research information. Approaches to automatically generating new lightweight deductive databases from existing ones, given database schemas, should be investigated. Work on agent based knowledge extraction (or data mining) from databases using Inductive Logic Programming [7],...
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BibTeX entry: (Update)
Davies, Winton H. E., and Edwards, Pete. Agent-Based Knowledge Discovery. In Working Notes of the AAAI Spring Symposium on Information Gathering from Heterogeneous, Distributed Environments. Stanford University, Stanford, CA, March, 1995. http://citeseer.ist.psu.edu/davies95agentbased.html More
@inproceedings{ davies95agentbased,
author = "Winton H. E. Davies and Pete Edwards",
title = "Agent-Based Knowledge Discovery",
booktitle = "{AAAI} Spring Symposium on Information Gathering",
publisher = "~",
address = "~",
editor = "~",
year = "1995",
url = "citeseer.ist.psu.edu/davies95agentbased.html" }
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