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Knowledge Discovery in Databases, [IEE Colloquium on]

Date 2 Feb 1995

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Displaying Results 1 - 8 of 8
  • Knowledge discovery in an infertility database using artificial neural networks

    Publication Year: 1995, Page(s):7/1 - 7/3
    Cited by:  Papers (1)
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (188 KB)

    Databases are complex structures that may conceal implicit patterns of information that cannot be easily discovered by conventional analysis and interrogation methods. This situation can be exacerbated as the database grows in size, and the data therein grows in complexity. Discovery of patterns and trends in such cases requires database query methods far in advance of those traditionally used. Su... View full abstract»

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  • Discovering knowledge hidden in a chemical database using a commercially available data mining tool

    Publication Year: 1995, Page(s):6/1 - 6/5
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (300 KB)

    Describes DataMariner, a commercially available tool that is designed to facilitate the discovery of knowledge hidden in databases. The potential of the tool for scientific applications is illustrated via a case study. This is both the first application of this particular tool to a scientific domain and the first project to describe the application of data mining techniques to the analytical separ... View full abstract»

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  • Data mining applications in BT

    Publication Year: 1995, Page(s):5/1 - 5/4
    Cited by:  Patents (6)
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (340 KB)

    Presents a number of case studies demonstrating how data mining is being used within BT to discover valuable knowledge. The case studies highlight the use of these techniques, the wealth of information contained in databases and learning points encountered. The studies presented are in the following areas: (1) identifying faults on printed circuit boards; (2) discovering the organisational structu... View full abstract»

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  • Discovering knowledge from automatically gathered production machine data

    Publication Year: 1995, Page(s):4/1 - 4/5
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (280 KB)

    A system designed for the automated acquisition of knowledge for an expert system for process control has been applied to discovery of knowledge of automatically gathered production machine data. Data relating to the number of parts produced by a number of production machines has been provided. Meaningful information which is useful in terms of understanding the production process is derived from ... View full abstract»

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  • Database mining in the Northern Ireland Housing Executive

    Publication Year: 1995, Page(s):8/1 - 8/4
    Cited by:  Patents (1)
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (168 KB)

    Describes some work being carried out by the Database Mining Research Group [DMRG] within the School of Information and Software Engineering, at the University of Ulster, Jordanstown. In particular the authors outline how they have been investigating the use of data mining techniques on data sets from the Northern Ireland Housing Executive [NIHE]. NIHE are responsible for the management of the pub... View full abstract»

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  • Data mining with Clementine

    Publication Year: 1995, Page(s):1/1 - 1/5
    Cited by:  Papers (2)  |  Patents (1)
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (224 KB)

    Data mining is the extraction of useful information or knowledge from bodies of data. Data mining is also sometimes referred to as knowledge discovery in databases. Clementine is a comprehensive, integrated toolkit which provides active support for data mining in the form of neural network and rule induction learning techniques, passive support in the form of visualisation, statistical and browsin... View full abstract»

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  • How to do knowledge acquisition without completely annoying your expert

    Publication Year: 1995, Page(s):2/1 - 210
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (392 KB)

    A central problem in producing any expert system is the elucidation of the knowledge from the expert. However, there is a large source of knowledge that is often overlooked by the knowledge engineer, and that is information direct from the process that you are trying to model. Unfortunately this data, when in its raw form, is unusable by a standard expert system; what is needed is some way of extr... View full abstract»

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  • Towards automated knowledge acquisition for process plant diagnosis

    Publication Year: 1995, Page(s):3/1 - 3/4
    Cited by:  Patents (1)
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (248 KB)

    There exists a need for diagnostic monitoring systems to ensure safer operation of process plants. Although acquisition of plant knowledge for such systems would prove expensive and time-consuming using traditional techniques, we feel this could be significantly reduced by extracting the information directly from the data held in the CAD models used in plant design. Any additional knowledge requir... View full abstract»

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