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Title |
Evolution of new WARM using Likert Weight Measures(LWM) |
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Author |
N. Sudha, Santhosh Baboo |
| Citation |
Vol. 11 No. 5 pp. 70-75 |
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Abstract |
The field of data mining draws upon several roots, including statistics, machine learning, databases and high performance computing. Supplier selection is an important process which needs more expertise to select a supplier as the technology complexity has increased. Frequently as there is a change in the market it will be better if flexibility is maintained. Choosing the right method for supplier selection effectively leads to a reduction in purchase risk and increases the number of JIT suppliers and TQM production. AHP is a widely accepted multi criteria decision making model, which is suitable for supplier selection process. But AHP is required high computation power. In order to reduce more computation power, in this paper we introduced a new model called Likert Weight Meaure (LWM), which is considered to be a light weight supplier selection model. Likert model is globally accepted scaling factor for psychometric feedback. |
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Keywords |
Data Mining, Weighted Association Rule Mining, AHP, LWM |
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