普查資料之空間資料挖掘研究—以台北市便利商店區位分析為例

Chin-Te Jung; 榮峻德

請用此 Handle URI 來引用此文件： http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/38780

完整後設資料紀錄

DC 欄位	值	語言
dc.contributor.advisor	孫志鴻(Chih-Hong Sun)
dc.contributor.author	Chin-Te Jung	en
dc.contributor.author	榮峻德	zh_TW
dc.date.accessioned	2021-06-13T16:45:55Z	-
dc.date.available	2005-07-04
dc.date.copyright	2005-07-04
dc.date.issued	2005
dc.date.submitted	2005-06-28
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Fast Algorithm for Mining Association Rules, In Proceedings of the Twentieth VLDB Conference：487-499 Applebaum, W. 1968. Guideline to Store location research-with emphasis on supermarket, Massachusetts: Addison-Wesley. Bailey, T.C. and Gatrell, A.C. 1995. Interactive Spatial Analysis , Longman Scientific & Technical Barnett, V. and Lewis, T., eds. 1994. Outlier Statistical Data. New York：John Wiley. Burrough, P.A. and Frank, A.U. 1995. Concepts and paradigm in spatial information: are current geographical information systems truly generic ?, International Journal of Geographical Information Systems, 9(2)：101-116. Chawla, S., Shekhar, S., WU, W. and Ozesmi, U. 2000. Extending Data Mining for Spatial Applicatoins：A Case Study in Predicting Nest Locations , 2000 ACM SIGMOD Workshop on Research Issue in Data Mining and Knowledge Discovery, DMKD 2000：70-77 Egenhofer, M. J. 1991. 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Conf. on Knowledge Discovery and Data Mining, New York City, NY ：44-50. Ester, Martin, Kriegel, Hans-Peter, Sander, Jorg 1999. Knowledge Discovery in Spatial Databases, Lectures Notes in Computer Science：64-71. Fayyad, U. , Piatetsky-Shapiro, G., Smyth, P. and Uthurusamy, R. 1996a. Advances in Knowledge Discovery and Data Mining , AAAI/MIT Press, Menlo Park,CA Fayyad, U. , Piatetsky-Shapiro, G., Smyth, P. and Smyth, P. 1996b. The KDD process for extracting useful knowledge from volumn data, Communications of the ACM, 39(11)：27-34. Frawley, W. J., Paitetsky-Shapiro, G.. and Matheus, C.J. 1992. Knowledge Discovery in Database: An Overview, Ai Magazine, 13：57-70. Gruen, V. and Smith, L. 1960. Shopping Town U.S.A.: the Planning of Shopping Centers, New York: Van Nostrand Reinhold. Han, J. and Fu, Y. 1995. Discovery of Multiple-level Association Rules from Large Databases , Processings of the 21st International Conference on Very Large Databases：420-431 Han, J. and Kamber, M. 2000. 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dc.identifier.uri	http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/38780	-
dc.description.abstract	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。	zh_TW
dc.description.abstract	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.	en
dc.description.provenance	Made available in DSpace on 2021-06-13T16:45:55Z (GMT). No. of bitstreams: 1 ntu-94-R92228009-1.pdf: 9978994 bytes, checksum: 72a0e9bbd4eb45aeca443b88bfc242d7 (MD5) Previous issue date: 2005	en
dc.description.tableofcontents	第一章緒論.........................................1 第一節研究動機................................. ....1 第二節研究目的......................................4 第三節研究流程......................................5 第四節研究假設......................................8 第二章文獻回顧.....................................10 第一節知識發現與資料挖掘 (KDD & Data Mining)........10 第二節空間資料挖掘簡介 ( Spatial data mining).......16 第三節關連規則與空間關連規則........................27 第四節普查資料之相關研究............................33 第五節便利商店區位因子..............................43 第六節小結..........................................48 第三章研究方法.....................................49 第一節研究架構......................................49 第二節空間普查資料庫的建立..........................51 第三節資料預處理....................................64 第四節資料轉換......................................69 第五節資料挖掘......................................73 第四章研究結果與討論...............................75 第一節研究結果與討論................................75 第二節綜合討論......................................83 第五章便利商店選址決策支援系統.....................87 第一節系統概述......................................87 第二節系統設計流程..................................88 第三節系統展示......................................89 第六章結論與建議...................................93 第一節研究結論......................................93 第二節研究建議......................................95 參考文獻.............................................98 中文參考文獻.........................................98 英文參考文獻.........................................100 附錄一：空間因子分佈狀態圖...........................105 附錄二：普查因子分佈狀態圖...........................108
dc.language.iso	zh-TW
dc.title	普查資料之空間資料挖掘研究—以台北市便利商店區位分析為例	zh_TW
dc.title	Spatial Data Mining on Census Data — A Case Study for Location Analysis of Convenience Stores in Taipei City	en
dc.type	Thesis
dc.date.schoolyear	93-2
dc.description.degree	碩士
dc.contributor.oralexamcommittee	張康聰(Kang-Tsung Chang),周學政
dc.subject.keyword	空間資料挖掘,關聯規則,GIS,普查資料,區位分析,	zh_TW
dc.subject.keyword	Spatial Data Mining,Association Rules,GIS,Census Data,Location Analysis,	en
dc.relation.page	113
dc.rights.note	有償授權
dc.date.accepted	2005-06-29
dc.contributor.author-college	理學院	zh_TW
dc.contributor.author-dept	地理環境資源學研究所	zh_TW
顯示於系所單位：	地理環境資源學系

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