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題名 如何在資料庫中發掘空間性週期關聯規則--以便利商店交易資料為例
Data Mining of Spatial Cyclic Association Rules in Databases -- A Convenience Store Transaction Data Example作者 郭家佑
Guo, Jia-You貢獻者 楊亨利
Yang, Heng-Li
郭家佑
Guo, Jia-You關鍵詞 空間性週期關聯規則
資料發掘
交易資料庫
Spatial Cyclic Association Rules
Data Mining
Transaction Database日期 1999 上傳時間 18-Sep-2009 19:32:23 (UTC+8) 摘要 資料發掘目前在傳統關聯式資料庫相關議題上已有不少研究，但如果能再整合空間和時間要素進來，將可從資料中發掘出更明確、更具體的知識。以往常使用統計分析方法來分析空間資料，不幸的是，統計分析方法仍有許多問題亟待解決。而Han等人利用概念樹發掘「多層次關聯規則」的技術已相當成熟，值得學習。在時間方面，另外有學者提出「週期關聯規則」的觀念。於是本研究便想結合以上研究的優點，希望能創造出新的應用。 本研究試著將「空間特性」和「週期關聯規則」結合，提出「空間性週期關聯規則」的想法。首先從相關文獻中分別瞭解目前空間、時間資料發掘領域的研究現況，從而整合相關研究，提出研究架構。再以動態網頁技術配合假想的台北市便利商店交易資料庫，發展出一套雛型系統（目前只能作單一項目之間的關聯），以驗證本架構的可行性。最後提出進一步的研究建議，以供後續研究參考。
There have been a lot of research about data mining in relational database. We can mine more specific and concrete knowledge in transaction databases by further considering spatial and temporal dimension. Until now the statistical spatial analysis has been one common technique for analyzing spatial data. However , there are still many remaining problems. Han et al. used concept hierarchies to mine multiple-level association rules. Their ideas are great and worth our learning. On the other hand , some scholars proposed the notion of cyclic association rules. Therefore , we combine the merits of these researches to discover more meaningful knowledge. In this research , we try to integrate the ideas of spatial associations with cyclic association and propose the idea of spatial cyclic association rules. First , we survey these researches in the fields of spatial and temporal data mining. A framework is then proposed. Finally , we implement a prototype system in WWW ( 1-itemset and 2-itemset only now).參考文獻 參考文獻
〔1〕Abbod, T., Brown, K. and Noble, N.,“Providing Time-related Constrains for Conventional Databases,”Proc. 13th Int. Conf. Very Large Data Bases Brighton, UK, 1987, pp.167-175.
〔2〕Abel, D. J.,“SIRO-DBMS：A Database Tool-Kit For Geographical Information Systems,”International Journal of Geographical Information Systems, Vol. 3, No. 2, 1989, pp.103-116.
〔3〕Adhikary, J., Koperski, K. and Han, J.“Spatial Data Mining： Progress and Challenges,”SIGMOD`96 Workshop. on Research Issues on Data Mining and Knowledge Discovery (DMKD`96), Montreal, Canada, 1996.
〔4〕Adhikary, J., Koperski, K. and Han, J.“Mining Knowledge in Geographical Data,”to appear in Communications of ACM, 1998.
〔5〕Agrawal, R., Faloutsos, C. and Swami, A.“Efficient Similarity Search in Sequence Databases,”Proc. 4th Int. Conf. on Foundations of Data Organization and Algorithms, 1993.
〔6〕Agrawal, R., Imielinski, T. and Swami, A.“Mining Association Rules Between Sets of Items in Large Databases,”Proc. 1993 ACM-SIGMOD Int. Conf. Management of Data , Washington, D. C., 1993, pp. 207-216.
〔7〕Agrawal, R. and Srikant, R.,“Fast Algorithms for Mining Association Rules,”Proc.1994 Int. Conf. VLDB, Santiago, Chile , 1994, pp.487-499.
〔8〕Agrawal, R. and Srikant, R.,“Mining Sequential Patterns,”Proc.1995 Int. Conf. Data Engineering, Taipei, Taiwan, 1995, pp.3-14.
〔9〕Ahn, I.,“Towards an Implementation of Database Management Systems with Temporal Support,”Proc. 2nd Int. Conf. Data Engineering Los Angeles, CA, USA, 1986, pp.371-381.
〔10〕Allen, J. F.,“Towards a General Theory of Actions and Time,”Artif. Intell, Vol. 23, 1984, pp.123-154.
〔11〕Anderson, T. L.,“Modelling Time at the Conceptual Level,”Improving database useability and responsiveness Academic Press, New York, NY, USA, 1982.
〔12〕Aref, W.G. and Samet, H.,“Extending a DBMS with Spatial Operations,”Advances in Spatial Databases, 1991, pp.299-318.
〔13〕Bell, D., Anand, S. S. and Shapcott, C. M.,“Database Mining in Spatial Databases,”International Workshop on Spatial-Temporal Databases, 1994.
〔14〕Buchmann, A., Gunther, O., Smith, T. R. and Wang, Y.-F., eds., Design and Implementation of Large Spatial Database. Lecture Notes in Computer Science 409, Springer-Verlag, Berlin, 1990.
〔15〕Cai, Y., Cercone, N. and Han, J.,“Data-driven Discovery of Quantitative Rules in Relational Databases,”IEEE Trans, Knowledge and Data Eng., Vol. 5, 1993, pp.29-40.
〔16〕Carey, M., DeWeitt, D. and Vanderberg, S.,“A Data Model and Query Language for EXODUS,”Proceedings of the 1988 ACM-SIGMOD International Conference on Management of Data, Chicago, Vol. 17, 1988, pp.413-423.
〔17〕Chen, M. S., Han, J. and Yu, P. S.,“Data Mining：An Overview from Database Perspective,”IEEE Transactions Knowledge and Data Engineering, 1996, pp.866-883.
〔18〕Clifford, J. and Warren, D. S.,“Formal Semantics for Time in Databases,”ACM Trans. Database Syst., Vol. 8, No. 2, 1983, pp.214-254.
〔19〕Deux, O. et al.,“The Story of ,”IEEE Transactions on Knowledge and Data Engineering, Vol. 2, No. 1, 1990, pp.91-108.
〔20〕Dietterich, T. G. and Michalski, R. S.,“Discoverying Patterns in Sequences of Events,”Artificial Intelligence, Vol. 25, 1985.
〔21〕Egenhofer, Max J.“Spatial SQL： A Query and Presentation Language,”IEEE Transactions on Knowledge and Data Engineering ,Vol. 6, No. 1, 1994, pp.86-95.
〔22〕Fayyad, U., et al.“Automated Analysis of a Large Scale Sky Survey：The SKICAT System,”Proc. 1993 Knowledge Discovery in Databases Workshop, Washington, D. C., 1993, pp.1-13.
〔23〕Fayyad, U. M. and Smyth, P.,“Image Databases Exploration：Progress and Challenges,”Proc. 1993 Knowledge Discovery in Databases Workshop, Washington, D. C., 1993, pp.14-27.
〔24〕Fayyad, U. M., Piatetsky-Shapiro, G., Smyth, P. and Uthurusamy, R., editors, Advances in Knowledge Discovery and Data Mining, AAAI/MIT Press, Menlo Park, CA, 1996.
〔25〕Fotheringham, S. and Rogerson, P., Spatial Analysis and GIS, Taylor and Francis, 1994.
〔26〕Fu, Y. and Han, J.“Dynamic Generation and Refinement of Concept Hierarchies for Knowledge Discovery in Databases,”Proc. AAAI’94 Workshop on Knowledge Discovery in Databases（KDD’94）, Seattle, WA, 1994, pp.157-168.
〔27〕Gadia, S. K.,“Parametric Databases：Seamless Integration of Spatial, Temporal, Belief and Ordinary Data,”SIGMOD Record, Vol. 22, No. 1, 1993, pp.15-20.
〔28〕Gong, W., “Periodic Pattern Search on Time-Related Data Sets,”M. Sc, Thesis, Simon Fraster University, 1997.
〔29〕Guan, J. and Bell, D., Evidence Theory and its Applications, Vol. Ⅰ, North-Holland, 1991.
〔30〕Gunther, O. and Schek, H. J., eds., Advances in Spatial Database. Lecture Notes in Computer Science 525, Springer-Verlag, Berlin, 1991.
〔31〕Han, J., Cai, Y. and Cercone, N.,“Data-Driven Discovery of Quantitative Rules in Relational Databases,”IEEE Transactions on Knowledge and Data Engineering, Vol. 5, No. 1, 1993, pp.29-40.
〔32〕Han, J., Cai, Y., Cercone, N. and Huang Y.,“Discovery of Data Evolution Regularities in Large Databases,”Journal of Computer and Software Engineering, Vol. 3, No. 1, 1995, pp.41-69.
〔33〕Han, J., Dong, G., and Yin, Y.,“Efficient Mining of Partial Periodic Patterns in Time Series Database”Proc. 1999 Int. Conf. on Data Engineering (ICDE`99),Australia, 1999, pp. 106-115.
〔34〕Han, J. and Fu, Y.,“Discovery of Multiple-Level Association Rules from Large Databases,”Proc. of 1995 Int. Conf. on Very Large Data Bases（VLDB’95）, Zich, Switzerland, 1995, pp.420-431.
〔35〕Knorr, E. and Ng, R. T.,“Applying Computational Geometry Concepts to Discovering Spatial Aggregate Proximity Relationships,”Technical Report, University of British Columbia, 1995.
〔36〕Koperski, K. and Han, J.“Discovery of Spatial Association Rules in Geographic Information Databases,”Proc. 4th Int`l Symp. on Large Spatial Databases (SSD’95), Portland, Maine, 1995, pp. 47-66.
〔37〕Lakshmanan, L.V.S., Ng, R., Han, J. and Pang, A.,“Optimization of Contrained Frequent Set Quries with 2-Variable Constraints, ”Proc. 1999 ACM-SIGMOD Conf. on Management of Data, Philadelphia, PA, June 1999, pp.157-168.
〔38〕Lu, W., Han, J. and Ooi, B. C.,“Discovery of General Knowledge in Large Spatial Databases,”Proc. Far East Workshop on Geographic Information Systems, Singapore, 1993, pp.275-289.
〔39〕Lum, V., Dadam, P., Erba, R. et al.,“Designing DBMS Support for the Temporal Dimension,”Proc. ACM-SIGMOD Int. Conf. Management of Data, 1984, pp.115-130.
〔40〕Major, J. and Mangano, J.,“Selecting among Rules Induced from a Hurricane Database,”Proc of 1993 KDD Workshop, Washington, D. C., 1993, pp.28-47.
〔41〕Marble, D. F. and Peuquet, D. J.,“ARC/INFO：An Example of a Contemporary Geographic Information System,”Introduction Readings In Geographic Information Systems, Marble, D. F. and Peuquet, D. J., eds. Taylor and Francis, London, 1990, pp.90-99.
〔42〕McDermott, D. V.,“A Temporal Logic for Reasoning about Processes and Plans,”Cognit.Sci., Vol. 6, 1982, pp.101-155.
〔43〕Michalski, R. S., Carbonnel, J. M. and Mitchell, T. M., editors, Machine Learning：An Artifical Intelligence Approach, Morgan Kaufmann, Los Altos, CA, 1983.
〔44〕Mitchell, T. M.,“Generalization as Search,”Artifical Intelligence, 1982, Vol. 18, pp.203-226.
〔45〕Navathe, S. B. and Ahmed, R.,“TSQL-A Language Interface for History databases,”Proceeding of the Conference on Temporal Aspects in Information Systems, AFCET, North-Holland, 1987, pp.113-128.
〔46〕Ng, R. and Han, J.,“Efficient and Effective Clustering Method for Spatial Data Mining,”Proc. 1994 Int. Conf. Very Large Data Bases, Santiago, Chile, September 1994, pp.144-155.
〔47〕Ng, R., Lakshmanan, L.V.S., Han, J. and Pang, A.,“Explorator Mining and Pruning Optimizations of Constrained Association Rules,”Proc. of 1998 ACM-SIGMOD Conf. On Management of Data,Settle, Washington, June 1998, pp.13-24.
〔48〕Ozden, B., Ramaswamy, S. and Silberschatz, A.,“Cyclic Association Rules,”Proc. of 1998 Int. Conf. Data Engineering（ICDE’98）, 1998, pp.412-421.
〔49〕Piatetsky-Shapiro, G. and Frawley, W. J., editors, Knowledge Discovery in Databases, AAAI/MIT Pres, Menlo Park, CA, 1991.
〔50〕Schilcher, M.,“Interactive Computer Graphic Data Processing in Cartography,”Computers ＆ Graphics, Vol. 9, No. 1, 1985, pp.57-66.
〔51〕Scholl, M. and Voisard, A.,“Object-Oriented Database Systems for Geographic Applications：An Example with ,”Geographic Database Management Systems, G. Gambosi, M. Scholl and H. W. Six, eds., Springer-Verlag, Berlin, 1992,pp. 103-137.
〔52〕Shaffer, C. A., Samet, H. and Nelson, R. C.,“QUILT： A Geographic Information System Based on Quadtrees,”International Journal of Geographical Information Systems, Vol. 4, No. 2, 1990,pp.103-131.
〔53〕Shaw, G. and Wheeler, D., Statistical Techniques in Geographical Analysis, London, David Fulton, 1994.
〔54〕Smyth, P., Burl, M. C., Fayyad, U. M. and Perona, P.,“Knowledge Discovery in Large Image Databases：Dealing with Uncertainties in Ground Truth,”Proc. of AAAI-94 Workshop on KDD, Seattle, WA, 1994, pp.109-120.
〔55〕Snodgrass, R. T. and Ahn, I.,“A Taxonomy of Time in Databases,”Proc. ACM-SIGMOD Int. Conf. Management of Data, Austin, TX, USA, 1985, pp.236-246.
〔56〕 Snodgrass, R. T. and Ahn, I.,“Temporal Databases,”IEEE Computer, Vol. 19, No. 9, 1986, pp.35-42.
〔57〕Spicgel, M., Schaum’s Outline Series of Theory and Problems of Statistics, McGraw Hill, 1996.
〔58〕Stolorz, P. et al.,“Fast Spatio-Temporal Data Mining of Large Geophysical Databases,”Proc. of the First International Conference on Data Mining KDD-95, Montreal, Canada, 1995, pp.300-305.
〔59〕Tansel, A U,“An Extension of Relational Algebra to Handle Time in Relational Databases,”Proc. ACM-SIGMOD Int. Conf. Management of Data, Austin, TX, USA, 1985, pp.247-265.
〔60〕Tomlin, C. D., Geographic Information Systems and Cartographic Modeling, Prentice Hall, Englewood Cliffs, N.J., 1990.
〔61〕Tufte, E. R.,“The Visual Display of Quantitative Information,”Graphics Press, Cheshire, Conn, 1983.
〔62〕Tufte, E. R.,“Envisioning Information,”Graphics Press, Cheshire, Conn, 1990.
〔63〕Vijlbrief, T. and van Oosterom, P.,“The GEO++ System：An Extensible GIS,”Proceedings of the 4th International Symposium on Spatial Data Handling, Charleston, Vol. 1, 1992, pp.40-50.
〔64〕Waugh, T. C. and Healey, R. G.,“The GEOVIEW Design：A Relational Data Base Approach to Geographical Data Handling,”International Journal of Geographical Information Systems, Vol. 1, No. 2, 1987, pp.101-118.
〔65〕Weiss, S. M. and Indurkhya, N., Predictive Data Mining：a Practical Guide, Morgan Kaufmann Publishers, San Francisco, Californic, 1998.
〔66〕Wu, S. and Manber, U.,“Fast Text Searching Allowing Errors,”Communications of the ACM, Vol. 35, 1992.
〔67〕Xia, B. B.,“Similarity Search in Time Series Data Sets,”M.Sc. thesis, Computing Science, Simon Fraser University, 1997.
〔68〕林幸怡（民國八十六年）“擴充先前知識以輔助資料發掘，”政治大學資訊管理研究所碩士論文。
〔69〕周學政、周天穎（民國八十六年），ArcView透視3.X，松岡電腦圖書資料股份有限公司。
〔70〕王國榮（民國八十七年），Active Server Pages ＆ Web資料庫，旗標出版股份有限公司。
〔71〕許建志、傅志雄（民國八十七年），精通Active Server Pages，靖宇資訊科技股份有限公司。
〔72〕李世傑（民國八十七年），Active Server Pages 2.0 網頁設計手冊，□峰資訊股份有限公司。描述 碩士
國立政治大學
資訊管理研究所
86356014
88資料來源 http://thesis.lib.nccu.edu.tw/record/#B2002001644 資料類型 thesis dc.contributor.advisor 楊亨利 zh_TW dc.contributor.advisor Yang, Heng-Li en_US dc.contributor.author (Authors) 郭家佑 zh_TW dc.contributor.author (Authors) Guo, Jia-You en_US dc.creator (作者) 郭家佑 zh_TW dc.creator (作者) Guo, Jia-You en_US dc.date (日期) 1999 en_US dc.date.accessioned 18-Sep-2009 19:32:23 (UTC+8) - dc.date.available 18-Sep-2009 19:32:23 (UTC+8) - dc.date.issued (上傳時間) 18-Sep-2009 19:32:23 (UTC+8) - dc.identifier (Other Identifiers) B2002001644 en_US dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/36763 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 資訊管理研究所 zh_TW dc.description (描述) 86356014 zh_TW dc.description (描述) 88 zh_TW dc.description.abstract (摘要) 資料發掘目前在傳統關聯式資料庫相關議題上已有不少研究，但如果能再整合空間和時間要素進來，將可從資料中發掘出更明確、更具體的知識。以往常使用統計分析方法來分析空間資料，不幸的是，統計分析方法仍有許多問題亟待解決。而Han等人利用概念樹發掘「多層次關聯規則」的技術已相當成熟，值得學習。在時間方面，另外有學者提出「週期關聯規則」的觀念。於是本研究便想結合以上研究的優點，希望能創造出新的應用。 本研究試著將「空間特性」和「週期關聯規則」結合，提出「空間性週期關聯規則」的想法。首先從相關文獻中分別瞭解目前空間、時間資料發掘領域的研究現況，從而整合相關研究，提出研究架構。再以動態網頁技術配合假想的台北市便利商店交易資料庫，發展出一套雛型系統（目前只能作單一項目之間的關聯），以驗證本架構的可行性。最後提出進一步的研究建議，以供後續研究參考。 zh_TW dc.description.abstract (摘要) There have been a lot of research about data mining in relational database. We can mine more specific and concrete knowledge in transaction databases by further considering spatial and temporal dimension. Until now the statistical spatial analysis has been one common technique for analyzing spatial data. However , there are still many remaining problems. Han et al. used concept hierarchies to mine multiple-level association rules. Their ideas are great and worth our learning. On the other hand , some scholars proposed the notion of cyclic association rules. Therefore , we combine the merits of these researches to discover more meaningful knowledge. In this research , we try to integrate the ideas of spatial associations with cyclic association and propose the idea of spatial cyclic association rules. First , we survey these researches in the fields of spatial and temporal data mining. A framework is then proposed. Finally , we implement a prototype system in WWW ( 1-itemset and 2-itemset only now). en_US dc.description.tableofcontents 目 錄 第壹章 緒 論 第一節 研究背景…………………………………………………………….1 第二節 研究動機、目的…………………………………………………….2 第三節 研究架構與方法…………………………………………………….3 第四節 研究限制…………………………………………………………….5 第貳章 文獻探討 第一節 空間資料庫簡介……………………………………………………. 6 一、主題圖（Thematic Maps）………………………………………….6 二、空間查詢……………………………………………………………..8 三、空間資料結構………………………………………………………..8 四、空間資料庫的架構…………………………………………………..9 第二節 空間資料發掘（Spatial Data Mining）的定義……………………. 11 一、定義…………………………………………………………………. . 11 二、背景…………………………………………………………………. 11 三、空間知識規則分類…………………………………………………. 11 第三節 空間資料發掘的方式…………………………………………….. 13 一、以統計為基礎的空間資料發掘……………………………………. 13 二、以一般化為基礎的空間資料發掘………………………………….14 三、利用分群技巧的空間資料發掘…………………………………….19 四、與空間關聯規則相關的空間資料發掘…………………………….20 五、利用CRH演算法的空間資料發掘………………………………….23 六、影像資料發掘……………………………………………………….24 七、其他空間資料發掘方法…………………………………………….25 第四節 時間資料庫簡介…………………………………………………... 25 一、時間查詢…………………………………………………………….25 二、時間資料結構……………………………………………………….26 第五節 時間資料發掘（Temporal Data Mining）的界定………………… 27 一、界定………………………………………………………………….27 二、時間知識規則分類………………………………………………….27 第六節 時間資料發掘的方式……………………………………………. . 31 一、以概念樹導向歸納分析技巧為基礎的時間資料發掘…………….31 二、與樣式（Pattern）相關的時間資料發掘………………………..33 三、以統計為基礎的時間資料發掘…………………………………….33 四、與週期關聯規則相關的時間資料發掘…………………………. 33 第七節 綜合評論……………………………………………………………35 一、空間與時間的結合…………………………………………………35 二、各種不同資料發掘方法的選用時機………………………………36 第參章 概念性系統架構 第一節 概念性系統架構內容定義與用途…………………………………44 一、使用者需求界定…………………………………………………….44 二、資料庫……………………………………………………………….46 三、概念樹……………………………………………………………….48 四、資料發掘方法……………………………………………………….49 五、知識規則展現……………………………………………………….54 六、多層次資料發掘…………………………………………………….55 第二節 演算法之整體流程……………………………………………….. .57 一、空間分析模組……………………………………………………….58 二、建立相關資料表格………………………………………………….60 三、時間性資料切割與抽象化………………………………………….61 四、發掘多數項目或多數項目之間的關聯…………………………….62 五、發掘週期…………………………………………………………….64 六、知識規則展現……………………………………………………….66 七、多層次資料發掘…………………………………………………….69 第三節 與以前研究的比較……………………………………………….. .72 一、空間資料處理方式………………………………………………….72 二、與週期關聯規則的比較…………………………………………….73 三、查詢語言的改進…………………………………………………….74 四、時間和空間發掘的整合…………………………………………….74 五、知識規則的表達…………………………………………………….75 六、執行效率…………………………………………………………….75 第肆章 概念性系統架構雛形實作 第一節 雛形系統設計……………………………………………………. . 76 第二節 系統建置環境介紹…………………………………………………77 一、系統開發技術 ………………………………………………………77 二、系統開發環境 ………………………………………………………83 三、系統操作環境 ………………………………………………………84 第三節 雛型系統發展模組介紹 ………………………………………84 第四節 雛型系統介紹 …………………………………………………105 一、執行本系統 ………………………………………………………105 二、雛型系統各模組操作說明 ………………………………………105 第五節 本架構下之其他可能建構工具 …………………………………131 一、網頁設計技術 ………………………………………………………131 二、空間分析技術 ………………………………………………………131 三、資料庫技術 ………………………………………………………131 第六節 雛型系統的執行效率 ……………………………………………132 第七節 系統維護與擴充 …………………………………………………135 第八節 與相關系統雛型比較 ……………………………………………135 一、Koperski and Han〔36〕的研究 …………………………………135 二、Ozden等人〔46〕的研究 ………………………………………136 三、雛型系統比較表 …………………………………………………136 第伍章 結論與建議 第一節 結 論 ……………………………………………………………137 第二節 後續研究的建議 …………………………………………………139 參考文獻 附錄一 台北市行政區圖 …………………………………………………148 附錄二 本研究假想之台北市12家便利商店分佈圖 …………………149 附錄三 本研究應用資料庫欄位說明 …………………………………150 附錄四 屬性值抽象化定義 ……………………………………………151 zh_TW dc.language.iso en_US - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#B2002001644 en_US dc.subject (關鍵詞) 空間性週期關聯規則 zh_TW dc.subject (關鍵詞) 資料發掘 zh_TW dc.subject (關鍵詞) 交易資料庫 zh_TW dc.subject (關鍵詞) Spatial Cyclic Association Rules en_US dc.subject (關鍵詞) Data Mining en_US dc.subject (關鍵詞) Transaction Database en_US dc.title (題名) 如何在資料庫中發掘空間性週期關聯規則--以便利商店交易資料為例 zh_TW dc.title (題名) Data Mining of Spatial Cyclic Association Rules in Databases -- A Convenience Store Transaction Data Example en_US dc.type (資料類型) thesis en dc.relation.reference (參考文獻) 參考文獻 zh_TW dc.relation.reference (參考文獻) 〔1〕Abbod, T., Brown, K. and Noble, N.,“Providing Time-related Constrains for Conventional Databases,”Proc. 13th Int. Conf. Very Large Data Bases Brighton, UK, 1987, pp.167-175. zh_TW dc.relation.reference (參考文獻) 〔2〕Abel, D. J.,“SIRO-DBMS：A Database Tool-Kit For Geographical Information Systems,”International Journal of Geographical Information Systems, Vol. 3, No. 2, 1989, pp.103-116. zh_TW dc.relation.reference (參考文獻) 〔3〕Adhikary, J., Koperski, K. and Han, J.“Spatial Data Mining： Progress and Challenges,”SIGMOD`96 Workshop. on Research Issues on Data Mining and Knowledge Discovery (DMKD`96), Montreal, Canada, 1996. zh_TW dc.relation.reference (參考文獻) 〔4〕Adhikary, J., Koperski, K. and Han, J.“Mining Knowledge in Geographical Data,”to appear in Communications of ACM, 1998. zh_TW dc.relation.reference (參考文獻) 〔5〕Agrawal, R., Faloutsos, C. and Swami, A.“Efficient Similarity Search in Sequence Databases,”Proc. 4th Int. Conf. on Foundations of Data Organization and Algorithms, 1993. zh_TW dc.relation.reference (參考文獻) 〔6〕Agrawal, R., Imielinski, T. and Swami, A.“Mining Association Rules Between Sets of Items in Large Databases,”Proc. 1993 ACM-SIGMOD Int. Conf. Management of Data , Washington, D. C., 1993, pp. 207-216. zh_TW dc.relation.reference (參考文獻) 〔7〕Agrawal, R. and Srikant, R.,“Fast Algorithms for Mining Association Rules,”Proc.1994 Int. Conf. VLDB, Santiago, Chile , 1994, pp.487-499. zh_TW dc.relation.reference (參考文獻) 〔8〕Agrawal, R. and Srikant, R.,“Mining Sequential Patterns,”Proc.1995 Int. Conf. Data Engineering, Taipei, Taiwan, 1995, pp.3-14. zh_TW dc.relation.reference (參考文獻) 〔9〕Ahn, I.,“Towards an Implementation of Database Management Systems with Temporal Support,”Proc. 2nd Int. Conf. Data Engineering Los Angeles, CA, USA, 1986, pp.371-381. zh_TW dc.relation.reference (參考文獻) 〔10〕Allen, J. F.,“Towards a General Theory of Actions and Time,”Artif. Intell, Vol. 23, 1984, pp.123-154. zh_TW dc.relation.reference (參考文獻) 〔11〕Anderson, T. L.,“Modelling Time at the Conceptual Level,”Improving database useability and responsiveness Academic Press, New York, NY, USA, 1982. zh_TW dc.relation.reference (參考文獻) 〔12〕Aref, W.G. and Samet, H.,“Extending a DBMS with Spatial Operations,”Advances in Spatial Databases, 1991, pp.299-318. zh_TW dc.relation.reference (參考文獻) 〔13〕Bell, D., Anand, S. S. and Shapcott, C. M.,“Database Mining in Spatial Databases,”International Workshop on Spatial-Temporal Databases, 1994. zh_TW dc.relation.reference (參考文獻) 〔14〕Buchmann, A., Gunther, O., Smith, T. R. and Wang, Y.-F., eds., Design and Implementation of Large Spatial Database. Lecture Notes in Computer Science 409, Springer-Verlag, Berlin, 1990. zh_TW dc.relation.reference (參考文獻) 〔15〕Cai, Y., Cercone, N. and Han, J.,“Data-driven Discovery of Quantitative Rules in Relational Databases,”IEEE Trans, Knowledge and Data Eng., Vol. 5, 1993, pp.29-40. zh_TW dc.relation.reference (參考文獻) 〔16〕Carey, M., DeWeitt, D. and Vanderberg, S.,“A Data Model and Query Language for EXODUS,”Proceedings of the 1988 ACM-SIGMOD International Conference on Management of Data, Chicago, Vol. 17, 1988, pp.413-423. zh_TW dc.relation.reference (參考文獻) 〔17〕Chen, M. S., Han, J. and Yu, P. S.,“Data Mining：An Overview from Database Perspective,”IEEE Transactions Knowledge and Data Engineering, 1996, pp.866-883. zh_TW dc.relation.reference (參考文獻) 〔18〕Clifford, J. and Warren, D. S.,“Formal Semantics for Time in Databases,”ACM Trans. Database Syst., Vol. 8, No. 2, 1983, pp.214-254. zh_TW dc.relation.reference (參考文獻) 〔19〕Deux, O. et al.,“The Story of ,”IEEE Transactions on Knowledge and Data Engineering, Vol. 2, No. 1, 1990, pp.91-108. zh_TW dc.relation.reference (參考文獻) 〔20〕Dietterich, T. G. and Michalski, R. S.,“Discoverying Patterns in Sequences of Events,”Artificial Intelligence, Vol. 25, 1985. zh_TW dc.relation.reference (參考文獻) 〔21〕Egenhofer, Max J.“Spatial SQL： A Query and Presentation Language,”IEEE Transactions on Knowledge and Data Engineering ,Vol. 6, No. 1, 1994, pp.86-95. zh_TW dc.relation.reference (參考文獻) 〔22〕Fayyad, U., et al.“Automated Analysis of a Large Scale Sky Survey：The SKICAT System,”Proc. 1993 Knowledge Discovery in Databases Workshop, Washington, D. C., 1993, pp.1-13. zh_TW dc.relation.reference (參考文獻) 〔23〕Fayyad, U. M. and Smyth, P.,“Image Databases Exploration：Progress and Challenges,”Proc. 1993 Knowledge Discovery in Databases Workshop, Washington, D. C., 1993, pp.14-27. zh_TW dc.relation.reference (參考文獻) 〔24〕Fayyad, U. M., Piatetsky-Shapiro, G., Smyth, P. and Uthurusamy, R., editors, Advances in Knowledge Discovery and Data Mining, AAAI/MIT Press, Menlo Park, CA, 1996. zh_TW dc.relation.reference (參考文獻) 〔25〕Fotheringham, S. and Rogerson, P., Spatial Analysis and GIS, Taylor and Francis, 1994. zh_TW dc.relation.reference (參考文獻) 〔26〕Fu, Y. and Han, J.“Dynamic Generation and Refinement of Concept Hierarchies for Knowledge Discovery in Databases,”Proc. AAAI’94 Workshop on Knowledge Discovery in Databases（KDD’94）, Seattle, WA, 1994, pp.157-168. zh_TW dc.relation.reference (參考文獻) 〔27〕Gadia, S. K.,“Parametric Databases：Seamless Integration of Spatial, Temporal, Belief and Ordinary Data,”SIGMOD Record, Vol. 22, No. 1, 1993, pp.15-20. zh_TW dc.relation.reference (參考文獻) 〔28〕Gong, W., “Periodic Pattern Search on Time-Related Data Sets,”M. Sc, Thesis, Simon Fraster University, 1997. zh_TW dc.relation.reference (參考文獻) 〔29〕Guan, J. and Bell, D., Evidence Theory and its Applications, Vol. Ⅰ, North-Holland, 1991. zh_TW dc.relation.reference (參考文獻) 〔30〕Gunther, O. and Schek, H. J., eds., Advances in Spatial Database. Lecture Notes in Computer Science 525, Springer-Verlag, Berlin, 1991. zh_TW dc.relation.reference (參考文獻) 〔31〕Han, J., Cai, Y. and Cercone, N.,“Data-Driven Discovery of Quantitative Rules in Relational Databases,”IEEE Transactions on Knowledge and Data Engineering, Vol. 5, No. 1, 1993, pp.29-40. zh_TW dc.relation.reference (參考文獻) 〔32〕Han, J., Cai, Y., Cercone, N. and Huang Y.,“Discovery of Data Evolution Regularities in Large Databases,”Journal of Computer and Software Engineering, Vol. 3, No. 1, 1995, pp.41-69. zh_TW dc.relation.reference (參考文獻) 〔33〕Han, J., Dong, G., and Yin, Y.,“Efficient Mining of Partial Periodic Patterns in Time Series Database”Proc. 1999 Int. Conf. on Data Engineering (ICDE`99),Australia, 1999, pp. 106-115. zh_TW dc.relation.reference (參考文獻) 〔34〕Han, J. and Fu, Y.,“Discovery of Multiple-Level Association Rules from Large Databases,”Proc. of 1995 Int. Conf. on Very Large Data Bases（VLDB’95）, Zich, Switzerland, 1995, pp.420-431. zh_TW dc.relation.reference (參考文獻) 〔35〕Knorr, E. and Ng, R. T.,“Applying Computational Geometry Concepts to Discovering Spatial Aggregate Proximity Relationships,”Technical Report, University of British Columbia, 1995. zh_TW dc.relation.reference (參考文獻) 〔36〕Koperski, K. and Han, J.“Discovery of Spatial Association Rules in Geographic Information Databases,”Proc. 4th Int`l Symp. on Large Spatial Databases (SSD’95), Portland, Maine, 1995, pp. 47-66. zh_TW dc.relation.reference (參考文獻) 〔37〕Lakshmanan, L.V.S., Ng, R., Han, J. and Pang, A.,“Optimization of Contrained Frequent Set Quries with 2-Variable Constraints, ”Proc. 1999 ACM-SIGMOD Conf. on Management of Data, Philadelphia, PA, June 1999, pp.157-168. zh_TW dc.relation.reference (參考文獻) 〔38〕Lu, W., Han, J. and Ooi, B. C.,“Discovery of General Knowledge in Large Spatial Databases,”Proc. Far East Workshop on Geographic Information Systems, Singapore, 1993, pp.275-289. zh_TW dc.relation.reference (參考文獻) 〔39〕Lum, V., Dadam, P., Erba, R. et al.,“Designing DBMS Support for the Temporal Dimension,”Proc. ACM-SIGMOD Int. Conf. Management of Data, 1984, pp.115-130. zh_TW dc.relation.reference (參考文獻) 〔40〕Major, J. and Mangano, J.,“Selecting among Rules Induced from a Hurricane Database,”Proc of 1993 KDD Workshop, Washington, D. C., 1993, pp.28-47. zh_TW dc.relation.reference (參考文獻) 〔41〕Marble, D. F. and Peuquet, D. J.,“ARC/INFO：An Example of a Contemporary Geographic Information System,”Introduction Readings In Geographic Information Systems, Marble, D. F. and Peuquet, D. J., eds. Taylor and Francis, London, 1990, pp.90-99. zh_TW dc.relation.reference (參考文獻) 〔42〕McDermott, D. V.,“A Temporal Logic for Reasoning about Processes and Plans,”Cognit.Sci., Vol. 6, 1982, pp.101-155. zh_TW dc.relation.reference (參考文獻) 〔43〕Michalski, R. S., Carbonnel, J. M. and Mitchell, T. M., editors, Machine Learning：An Artifical Intelligence Approach, Morgan Kaufmann, Los Altos, CA, 1983. zh_TW dc.relation.reference (參考文獻) 〔44〕Mitchell, T. M.,“Generalization as Search,”Artifical Intelligence, 1982, Vol. 18, pp.203-226. zh_TW dc.relation.reference (參考文獻) 〔45〕Navathe, S. B. and Ahmed, R.,“TSQL-A Language Interface for History databases,”Proceeding of the Conference on Temporal Aspects in Information Systems, AFCET, North-Holland, 1987, pp.113-128. zh_TW dc.relation.reference (參考文獻) 〔46〕Ng, R. and Han, J.,“Efficient and Effective Clustering Method for Spatial Data Mining,”Proc. 1994 Int. Conf. Very Large Data Bases, Santiago, Chile, September 1994, pp.144-155. zh_TW dc.relation.reference (參考文獻) 〔47〕Ng, R., Lakshmanan, L.V.S., Han, J. and Pang, A.,“Explorator Mining and Pruning Optimizations of Constrained Association Rules,”Proc. of 1998 ACM-SIGMOD Conf. On Management of Data,Settle, Washington, June 1998, pp.13-24. zh_TW dc.relation.reference (參考文獻) 〔48〕Ozden, B., Ramaswamy, S. and Silberschatz, A.,“Cyclic Association Rules,”Proc. of 1998 Int. Conf. Data Engineering（ICDE’98）, 1998, pp.412-421. zh_TW dc.relation.reference (參考文獻) 〔49〕Piatetsky-Shapiro, G. and Frawley, W. J., editors, Knowledge Discovery in Databases, AAAI/MIT Pres, Menlo Park, CA, 1991. zh_TW dc.relation.reference (參考文獻) 〔50〕Schilcher, M.,“Interactive Computer Graphic Data Processing in Cartography,”Computers ＆ Graphics, Vol. 9, No. 1, 1985, pp.57-66. zh_TW dc.relation.reference (參考文獻) 〔51〕Scholl, M. and Voisard, A.,“Object-Oriented Database Systems for Geographic Applications：An Example with ,”Geographic Database Management Systems, G. Gambosi, M. Scholl and H. W. Six, eds., Springer-Verlag, Berlin, 1992,pp. 103-137. zh_TW dc.relation.reference (參考文獻) 〔52〕Shaffer, C. A., Samet, H. and Nelson, R. C.,“QUILT： A Geographic Information System Based on Quadtrees,”International Journal of Geographical Information Systems, Vol. 4, No. 2, 1990,pp.103-131. zh_TW dc.relation.reference (參考文獻) 〔53〕Shaw, G. and Wheeler, D., Statistical Techniques in Geographical Analysis, London, David Fulton, 1994. zh_TW dc.relation.reference (參考文獻) 〔54〕Smyth, P., Burl, M. C., Fayyad, U. M. and Perona, P.,“Knowledge Discovery in Large Image Databases：Dealing with Uncertainties in Ground Truth,”Proc. of AAAI-94 Workshop on KDD, Seattle, WA, 1994, pp.109-120. zh_TW dc.relation.reference (參考文獻) 〔55〕Snodgrass, R. T. and Ahn, I.,“A Taxonomy of Time in Databases,”Proc. ACM-SIGMOD Int. Conf. Management of Data, Austin, TX, USA, 1985, pp.236-246. zh_TW dc.relation.reference (參考文獻) 〔56〕 Snodgrass, R. T. and Ahn, I.,“Temporal Databases,”IEEE Computer, Vol. 19, No. 9, 1986, pp.35-42. zh_TW dc.relation.reference (參考文獻) 〔57〕Spicgel, M., Schaum’s Outline Series of Theory and Problems of Statistics, McGraw Hill, 1996. zh_TW dc.relation.reference (參考文獻) 〔58〕Stolorz, P. et al.,“Fast Spatio-Temporal Data Mining of Large Geophysical Databases,”Proc. of the First International Conference on Data Mining KDD-95, Montreal, Canada, 1995, pp.300-305. zh_TW dc.relation.reference (參考文獻) 〔59〕Tansel, A U,“An Extension of Relational Algebra to Handle Time in Relational Databases,”Proc. ACM-SIGMOD Int. Conf. Management of Data, Austin, TX, USA, 1985, pp.247-265. zh_TW dc.relation.reference (參考文獻) 〔60〕Tomlin, C. D., Geographic Information Systems and Cartographic Modeling, Prentice Hall, Englewood Cliffs, N.J., 1990. zh_TW dc.relation.reference (參考文獻) 〔61〕Tufte, E. R.,“The Visual Display of Quantitative Information,”Graphics Press, Cheshire, Conn, 1983. zh_TW dc.relation.reference (參考文獻) 〔62〕Tufte, E. R.,“Envisioning Information,”Graphics Press, Cheshire, Conn, 1990. zh_TW dc.relation.reference (參考文獻) 〔63〕Vijlbrief, T. and van Oosterom, P.,“The GEO++ System：An Extensible GIS,”Proceedings of the 4th International Symposium on Spatial Data Handling, Charleston, Vol. 1, 1992, pp.40-50. zh_TW dc.relation.reference (參考文獻) 〔64〕Waugh, T. C. and Healey, R. G.,“The GEOVIEW Design：A Relational Data Base Approach to Geographical Data Handling,”International Journal of Geographical Information Systems, Vol. 1, No. 2, 1987, pp.101-118. zh_TW dc.relation.reference (參考文獻) 〔65〕Weiss, S. M. and Indurkhya, N., Predictive Data Mining：a Practical Guide, Morgan Kaufmann Publishers, San Francisco, Californic, 1998. zh_TW dc.relation.reference (參考文獻) 〔66〕Wu, S. and Manber, U.,“Fast Text Searching Allowing Errors,”Communications of the ACM, Vol. 35, 1992. zh_TW dc.relation.reference (參考文獻) 〔67〕Xia, B. B.,“Similarity Search in Time Series Data Sets,”M.Sc. thesis, Computing Science, Simon Fraser University, 1997. zh_TW dc.relation.reference (參考文獻) 〔68〕林幸怡（民國八十六年）“擴充先前知識以輔助資料發掘，”政治大學資訊管理研究所碩士論文。 zh_TW dc.relation.reference (參考文獻) 〔69〕周學政、周天穎（民國八十六年），ArcView透視3.X，松岡電腦圖書資料股份有限公司。 zh_TW dc.relation.reference (參考文獻) 〔70〕王國榮（民國八十七年），Active Server Pages ＆ Web資料庫，旗標出版股份有限公司。 zh_TW dc.relation.reference (參考文獻) 〔71〕許建志、傅志雄（民國八十七年），精通Active Server Pages，靖宇資訊科技股份有限公司。 zh_TW dc.relation.reference (參考文獻) 〔72〕李世傑（民國八十七年），Active Server Pages 2.0 網頁設計手冊，□峰資訊股份有限公司。 zh_TW
