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Title:
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GRID-BASED HIERARCHICAL CLUSTERING FOR SPATIAL RESOURCE ALLOCATION |
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Author(s):
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Liyang Liu, Simon Fong, Andy Ip |
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ISBN:
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978-972-8939-46-5 |
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Editors:
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Piet Kommers and Pedro Isaías |
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Year:
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2011 |
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Edition:
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Single |
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Keywords:
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Resource allocation, thinning algorithm, grid-based clustering, hierarchical clustering. |
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Type:
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Short Paper |
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First Page:
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513 |
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Last Page:
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517 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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The problem of allocating resources in spatial locations such as within an urban city or large regions in geographical sense has attracted much research efforts recently. Some applications include but not limit to city-planning for examples of building patrol stations in a city, establishing medical clinics or schools in a town, deploying guards for security patrol in a zone, and budgeting on the quantity of street lamps to lit up an urban area. These problems are generalized as spatial resource allocation, where they commonly share the characteristics of meeting certain demands by a limited amount of resources. The demands are usually distributed, unevenly in a confined spatial area. Traditionally clustering algorithms in data mining were used to solve these problems. In this paper, we proposed a grid-based hierarchical clustering approach that was designed specifically for this kind of resource allocation decision-support. The grid-based feature makes the data extraction process which is usually from maps efficient. The hierarchy of clusters as outputs provides an advantage over normal clustering techniques because the resultant clusters can be zoomed in or out in different resolutions or abstractions at will. |
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