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Framework for distributed knowledge discovery systems embedded in extended enterprise

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posted on 18.07.2018 by Elena I. Neaga
One of the foremost challenges facing manufacturing industry nowadays is the large-scale integration of their enterprise systems, along with their associated models, data and information. The enterprise applications generate large amounts of data which are a valuable asset and potentially an important source of new information and knowledge for improving the business of the enterprise, gaining competitive advantage in fierce markets and coping with changes and managerial complexity. The research reported in the thesis is focused on the modelling, design, development and implementation of knowledge discovery and data mining systems, by considering multiple views including knowledge, mining, information, data and application views defined at the level of enterprise reference architecture. [Continues.]

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Publisher

© Elena Irina Neaga

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Publication date

2003

Notes

A Doctoral Thesis. Submitted in partial fulfilment of the requirements for the award of Doctor of Philosophy at Loughborough University.

Language

en

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