由於戶口、工商普查資料可以真實的反應區域裡的社會經濟情況,所以不管是政府部門或者是私人企業都可以用來作為規劃以及分析的依據。便利商店所位在區域的普查資料,即是提供最基本顧客來源的基礎資料之一,並且便利商店最關鍵的成功因素,即是在於「區位」,如何有效的從大量的普查或著是空間資料中分析便利商店的區位,並且歸納出有用的知識出來,已是急迫且必須的。 故本研究整合了2000年台北市戶口普查資料、2001年台北市工商普查資料以及與台北市便利商店相關的空間資料,並利用台北市土地利用現況調查資料以及台北市門牌地址點資料,將2001年工商普查資料從現行最小統計單元的「里」分派到與戶口普查資料對應的「普查區」空間單元中,成為台北市普查區的空間普查資料庫。並且使用資料挖掘技術中的關聯規則方法,應用在台北市便利商店區位分析中,挖掘出便利商店座落區域中的普查資料與其他空間資料的關連性,並將影響便利商店區位因子加以量化描述,找出平常所沒有注意到、有趣的關聯規則。最後整合GIS,將重要的規則在空間上呈現,幫助後續決策者,重新評估便利商店的區位,或著在新設置便利商店的區位上,能夠有更進一步的參考。
Census data often accurately reflect the socio-economic trends and characteristics of the region under survey, they serve as a useful planning tool for both the government and the private enterprises. In this research, we collect the Taipei census data in 2000, the industrial census data in 2001, and the present Taipei geospatial data into the Spatial Census Database. In order to converse the industrial census data in 2001 into the same units of Taipei Census Database, we develop a data conversion model which use the land use data and “Geographic Data Management System of Building Address” developed by Taipei Municipal Government to complete it. Such database is analyzed by the association rules of data mining in the location of the existing convenience stores in the Taipei area. The analysis unveils the interesting association rules among census, demographics and the location of convenience stores. Finally, this research incorporates geographic information system (GIS) technology to map the result of the analysis so as to provide a spatial representation that will be more easily understood.