本研究利用空間資料探勘的方法，分析臺北市政府1999 市民熱線在2010 年4 月、5 月與6 月的違規停車紀錄，並試著瞭解其發生位置與整體趨勢。平均最近鄰 分析與核密度估計的結果顯示，違規停車紀錄確實呈現顯著的空間群聚現象，最主 要的高密度區域在中正區的北部、中正區的西部、松山區的中部、信義區的西北部 與大安區的中南部。總之，本研究呈現空間資料探勘方法如何協助政府發掘資料背 後所隱藏的民意知識，以作為未來擬定或支援決策的參考。

Using spatial data mining method, this study analyzed parking violation cases from April to June in 2010, which were provided by 1999 citizen hotline of Taipei City Government, and tried to understand the locations of incidents and the trend. The results of Average Nearest Neighbor and Kernel Density Estimation revealed that parking violation cases did exhibit significant spatial dependence in Taipei City, and the areas with higher density of parking violation are included northern and western Zhongzheng, middle Songshan, northwestern Xinyi, and middle southern Da'an. In general, this study presented how Spatial Data mining can help the government to find the public opinion knowledge hidden in the data in order to further develop strategies and support policies.