Discovering Trends in Large Datasets Using Neural Networks

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dc.contributor.authorKaikhah, Khosrow
dc.contributor.authorDoddameti, Sandesh
dc.date.accessioned2012-02-24T10:17:53Z
dc.date.available2012-02-24T10:17:53Z
dc.date.issued2006-02-01
dc.description.abstractA novel knowledge discovery technique using neural networks is presented. A neural network is trained to learn the correlations and relationships that exist in a dataset. The neural network is then pruned and modified to generalize the correlations and relationships. Finally, the neural network is used as a tool to discover all existing hidden trends in four different types of crimes (murder, rape, robbery, and auto theft) in US cities as well as to predict trends based on existing knowledge inherent in the network.
dc.description.departmentComputer Science
dc.formatText
dc.format.extent23 pages
dc.format.medium1 file (.pdf)
dc.identifier.citationKaikhah, K. & Doddameti, S. (2006). Discovering trends in large datasets using neural networks. Applied Intelligence, 24(1), pp. 51-60.
dc.identifier.doihttps://doi.org/10.1007/s10489-006-6929-9
dc.identifier.urihttps://hdl.handle.net/10877/3817
dc.language.isoen
dc.publisherSpringer
dc.sourceApplied Intelligence: The International Journal of Artificial Intelligence, Neural Networks, and Complex Problem-solving Technologies, February 2006, Vol. 24, No. 1, pp. 51-60.
dc.subjectlarge datasets
dc.subjectneural networks
dc.subjectknowledge discovery
dc.subjectComputer Science
dc.titleDiscovering Trends in Large Datasets Using Neural Networks
dc.typeArticle

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