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Framework for distributed knowledge discovery systems embedded in extended enterprise
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 importa...
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| Format: | Default Thesis |
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2003
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| Online Access: | https://hdl.handle.net/2134/33990 |
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| _version_ | 1818169486376697856 |
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| author | Elena I. Neaga |
| author_facet | Elena I. Neaga |
| author_sort | Elena I. Neaga (7201652) |
| collection | Figshare |
| description | 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.] |
| format | Default Thesis |
| id | rr-article-9525254 |
| institution | Loughborough University |
| publishDate | 2003 |
| record_format | Figshare |
| spelling | rr-article-95252542003-01-01T00:00:00Z Framework for distributed knowledge discovery systems embedded in extended enterprise Elena I. Neaga (7201652) Mechanical engineering not elsewhere classified untagged Mechanical Engineering not elsewhere classified 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.] 2003-01-01T00:00:00Z Text Thesis 2134/33990 https://figshare.com/articles/thesis/Framework_for_distributed_knowledge_discovery_systems_embedded_in_extended_enterprise/9525254 CC BY-NC-ND 4.0 |
| spellingShingle | Mechanical engineering not elsewhere classified untagged Mechanical Engineering not elsewhere classified Elena I. Neaga Framework for distributed knowledge discovery systems embedded in extended enterprise |
| title | Framework for distributed knowledge discovery systems embedded in extended enterprise |
| title_full | Framework for distributed knowledge discovery systems embedded in extended enterprise |
| title_fullStr | Framework for distributed knowledge discovery systems embedded in extended enterprise |
| title_full_unstemmed | Framework for distributed knowledge discovery systems embedded in extended enterprise |
| title_short | Framework for distributed knowledge discovery systems embedded in extended enterprise |
| title_sort | framework for distributed knowledge discovery systems embedded in extended enterprise |
| topic | Mechanical engineering not elsewhere classified untagged Mechanical Engineering not elsewhere classified |
| url | https://hdl.handle.net/2134/33990 |