Extracting Understanding From Big Data to Support Supply Chain innovation

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Chen, Fan (2013) Extracting Understanding From Big Data to Support Supply Chain innovation. [Dissertation (University of Nottingham only)] (Unpublished)

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Abstract

This dissertation is concerned with build an analytic infrastructure to support Big Data analytic. It describes the development and testing of an analytic infrastructure. This method is a combination of connectance concept, deduction graph and data mining technique. This model supports vividly alternative developing processes by the deduction graph, so the decision-makers have the clear view about the expansion of the competences sets. The analytic infrastructure provides more knowledge, skills and technologies to enhance the capability through data mining technique.

The analytic infrastructure is efficient to support decision makers by offering more alternative choices and suggesting the optimal solution. This model provides more alternative developing processes option for decision makers. This model is suitable for solving manufacturing problems.

Item Type: Dissertation (University of Nottingham only)
Depositing User: EP, Services
Date Deposited: 07 Mar 2014 15:37
Last Modified: 19 Oct 2017 13:35
URI: https://eprints.nottingham.ac.uk/id/eprint/26626

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