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Intelligent Database Systems Lab Presenter: YU-TING LU Authors: Vittorio Carlei, Massimiliano Nuccio 2014. PRL Mapping industrial patterns in spatial agglomeration: A SOM approach to Italian industrial districts
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Intelligent Database Systems Lab Outlines Motivation Objectives Methodology Experiments Conclusions Comments
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Intelligent Database Systems Lab Motivation IDs are traditionally identified by indexes which measure the physical concentration of firms belonging to a given industry, but are unable to seize the overall productive structure of the local economy.
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Intelligent Database Systems Lab Objectives The methodology can be applied to different sizes of economic regions, to different industries and at different levels of industry classification. The topological clustering provided by the SOM is able to define industrial patterns and also can measure the relative relevance of a given industry with Component Planes.
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Intelligent Database Systems Lab Methodology
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Intelligent Database Systems Lab Methodology
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Intelligent Database Systems Lab Methodology
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Intelligent Database Systems Lab Experiments
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Intelligent Database Systems Lab Experiments - The case of the Italian Clothing Industry
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Intelligent Database Systems Lab Experiments - Concentration vs. RIR
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Intelligent Database Systems Lab Conclusions This paper contributes to investigate the process of regionalization of economic activities based on the geographic distribution of labour factor as a proxy of the local supply of human capital.
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Intelligent Database Systems Lab Comments Advantages - Identify different forms of spatial agglomeration and local patterns of industrial Applications - Self-Organizing Map - Analysis of Industry agglomeration
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