Experience mining based innovative method for promoting urban sustainability

Abstract

The promotion of sustainable urbanization has generated a growing number of best practice cases, which has led to the development of a prototype of an Experience Mining System (ExMS) for better use of the valuable experience embodied in these best practices. This paper presents an innovative method for the effective application of the experience mining system thus to promote the urban sustainability. It is considered essential to appreciate the urban features when ExMS is used to mine effective experiences for improving the sustainability of a specific urban area. For this purpose, this paper introduces the measure of similarity between a concerned case and those cases reported in an ExMS database in order to ensure the effectiveness of mining good experience. The method presented in this paper, it helps to find out useful experiences from existing best sustainable urbanization practices by considering the similarity between the case concerned and the sample best practices. The similarity is measured from six perspectives of urban features, including landform, climate, urban scale, development level, Gini coefficient, and GDP performance. The value formats of these six urban features include crisp symbol, crisp number, interval number, and fuzzy linguistic variable. A hybrid similarity measure will therefore guide the process in mining effective experiences for the promotion of urban sustainability.