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題名 網頁資料發掘技術導入網站經營者之研究－以入口網站之分類索引服務為例
作者 林繼文
貢獻者 裘錦天
林繼文
關鍵詞 資料發掘
商業智慧
網站經營者
入口網站
流量指標
日期 2001
上傳時間 18-四月-2016 16:26:33 (UTC+8)
摘要 網頁資料發掘為從全球資訊網所發現或分析而得的有用資訊。若能在訪客所留下的紀錄中，分析出這些資訊，對於經營者而言是一個重要的決策依據。入口網站幾乎僅以廣告為主要收入，如何借重網頁資料發掘技術來了解網路使用者的行為，作為加強網站內容設計與經營方向的參考，當為目前經營者所關心的重要課題。本研究將導入知識的觀點，利用商業智慧中的資料發掘技術，實際分析網站的紀錄資料，研究網頁資料發掘技術對於網站經營者的幫助，進而為企業組織帶來競爭優勢。
參考文獻 [1] 何光國，圖書資訊組織原理，三民書局，民國79年，頁25至26。
     [2] 吳琮璠、謝清佳，資訊管理 理論與實務，民國85年，頁1-10至1-12。
     [3] 邵敏華，建構開放性之企業知識管理系統，國立政治大學資訊管理研究所碩士論文，民國87年。
     [4] 馮國卿，知識管理在電子圖書館應用之研究，國立政治大學圖書資訊研究所碩士論文，民國87年。
     [5] 劉容志，IBM Software Update，民國87年10月。
     [6] 謝清俊，公共資訊系統概說，圖書館與資訊研究論文集，漢美書局，民國85年，頁163。
     [7] 樓玉玲，以資料發掘技術分析政大通識課程，國立政治大學資訊管理研究所碩士論文，民國87年。
     [8] 主題網際資訊，Visitor Relationship Management – WebTrends Enterprise Reporting Server，客戶關係管理研討會，民國89年五月。
     [9] Adriaans, P. and Zantinge, D., Data Mining, Addison-Wesley, 1996.
     [10] Bellinger, G., “Knowledge Management”, http://www.outsights.com/systems/kmgmt/kmgmt.htm
     [11] Berry, M. J. A. and Linoff, G., Data Mining Technique For Marketing, Sale, And Customer Support, Wiley Computer, 1997.
     [12] Cabena, P., Hadjinian, P., Stadler, R., Verhees, J., and Zanasi, A., Discovering Data Mining – From Concept to Implementation, Prentice Hall Ptr, 1998.
     [13] Codd, E. F., “Providing OLAP to User- Analysis: An IT Mandate”, Sep. 1998, http://www.arborsoft.com/essbase/wht_ppr/coodcl.html
     [14] Connelly, R., McNeill, R., and Mosimann, R., The Multi Dimensional Manager, Cognos, Oct. 1996.
     [15] Cooley, R., Mobasher, B., and Srivastava, J., “Data Preparation for Mining World Wide Web Browsing Patterns”, Knowledge and Information Systems, Vol. 1, No. 1, 1999.
     [16] Davis, M. C., “Knowledge Management”, Information Strategy: The Executive’s Journal, Fall 1998.
     [17] Harris, D.B., “Creating A Knowledge Centric Information Technology Environment”, Sep. 1998, http://www.htcs.com/ckc.html
     [18] Drucker, P. F., Post-Capitalist Society, Harper Collins, 1993, pp. 25-30.
     [19] Edvinsson, L. and Sullivan, P., “Developing a Model for Managing Intellectual Capital”, European Management Journal, Vol. 14. No. 4, Aug. 1996, pp. 356-364.
     [20] Fayyad, U. M., “Data Mining and Knowledge Discovery: Making Sense Out of Data”, IEEE Expert, Oct. 1996, pp. 20-25.
     [21] Fayyad, U. M. and Ramasamy, U., “Data Mining and Knowledge Discovery in Database”, Communications of The ACM, Nov. 1996, Vol. 39, pp. 24-26.
     [22] Frawley, W. J., Piatesky-Shapiro, and Matheus, G. C. J., Knowledge Discovery in Database: An Overview, AAAI/MIT Press, 1991, pp. 1-30.
     [23] Fuld, L. M., The New Competitor Intelligence: The Complete Resource for Finding, Analyzing, and Using Information about Your Competitors, NY: Wiley, 1995.
     [24] Gilad, B., The Art and Science of Business Intelligence Analysis: Business Intelligence Theory, Principles, Practices, and Uses”, ed. Gilad, B. and Herring, J. P., Jai Press Inc., 1996, p.4.
     [25] Gloede, C., “Designing A Business Intelligence System”, Midrange Systems, Dec. 12, 1997, pp. 49-50.
     [26] Greening, D. R., “Data Mining on the Web - There`s Gold in that Mountain of Data”, http://www.webtechniques.com/archives/2000/01/greening/
     [27] Grupe, F. H. and Owrang, M. M., “Data Base Mining Discovering New Knowledge and Cooperative Advantage,” Information Systems Management, Fall 1995, pp.26-31.
     [28] Hildebrand, C., “All Aboard the BI Bandwagon”, CIO, Vol.11, Jul. 15, 1998, p. 16.
     [29] IBM, “IBM Data Management White Paper - If data were money, would you manage it differently?”, 1999, http://www.software.ibm.com/data/busn-intel/biadinsert
     [30] Inmon, W. H., Building the Data Warehouse, Wellesley, MA:QED Technical Publishing Group, 1992.
     [31] Komenar, M., Electronic Marketing, Wiley Computer Publishing, 1993, pp.80-81.
     [32] Malhotra, Y., “World Wide Web Virtual Library on Knowledge Management”, Aug. 1998, http://www.brint.com/km/
     [33] Microsoft Sales Online!, Microsoft SQL Server Questions and Answers: “What is a data warehouse?”, Jan.1, 1997, http://www.microsoft.com/salesinfo/qa/mssq1013.html
     [34] Mobasher, B., Cooley, R., and Srivastava, J., “Web Mining: Information and Pattern Discovery on the World Wide Web”, http://www-users.cs.umn.edu/~mobasher/webminer/survey/survey.html
     [35] Nonaka, I., “The Knowledge Creating Company”, Harvard Business Review, Nov.-Dec., 1991, pp. 96-104.
     [36] Nonaka, I. and Takeuchi, H., The Knowledge Creating Company: How Japanese Companies Create the Dynamics of Innovation, Oxford University Express, 1995, p. 54.
     [37] OLAP Council, “OLAP and OLAP Server Definitions,” Sep. 1998, http://www.olapcouncil.org/research/
     [38] Paitetsky-Shapiro, G., Discovery, Analysis, and Presentation of Strong Rules”, Knowledge Discovery in Database, ed. G. Piatetsky-Shapiro and Frawley, W. J., CA: AAAI/MIT Press, 1991, pp. 229-238.
     [39] Shaw, R. and Stone, M., Database Marketing, Aldershot: Gwer Publishing, 1990.
     [40] Spek, R. van der and Spijkervet, A., “Knowledge Management: Dealing Intelligency with Knowledge”, Knowledge Management and Its Integrative Elements, ed. Liebowitz, J. and Wilcox, L. C. , NY: CRC Press, 1997, p. 40.
     [41] Vedder, R. G. and Vanecek, M. T., “Competitive Intelligence for IT Resource Planning: Some Lessons Learned”, Information Strategy: The Executive’s Journal, Fall 1998, pp. 29-36.
     [42] Wilson, R. F., “Web Marketing Today”, Jul. 1, 2000, http://www.wilsonweb.com/articles/bannerad.htm
     [43] Zanasi, A., “Competitive Intelligence through Data Mining Public Sources”, Competitive Intelligence Review, Vol. 9, 1998, pp. 44-54.
描述 碩士
國立政治大學
資訊管理學系
86356001
資料來源 http://thesis.lib.nccu.edu.tw/record/#A2002001575
資料類型 thesis
dc.contributor.advisor 裘錦天zh_TW
dc.contributor.author (作者) 林繼文zh_TW
dc.creator (作者) 林繼文zh_TW
dc.date (日期) 2001en_US
dc.date.accessioned 18-四月-2016 16:26:33 (UTC+8)-
dc.date.available 18-四月-2016 16:26:33 (UTC+8)-
dc.date.issued (上傳時間) 18-四月-2016 16:26:33 (UTC+8)-
dc.identifier (其他 識別碼) A2002001575en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/85360-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 資訊管理學系zh_TW
dc.description (描述) 86356001zh_TW
dc.description.abstract (摘要) 網頁資料發掘為從全球資訊網所發現或分析而得的有用資訊。若能在訪客所留下的紀錄中，分析出這些資訊，對於經營者而言是一個重要的決策依據。入口網站幾乎僅以廣告為主要收入，如何借重網頁資料發掘技術來了解網路使用者的行為，作為加強網站內容設計與經營方向的參考，當為目前經營者所關心的重要課題。本研究將導入知識的觀點，利用商業智慧中的資料發掘技術，實際分析網站的紀錄資料，研究網頁資料發掘技術對於網站經營者的幫助，進而為企業組織帶來競爭優勢。zh_TW
dc.description.tableofcontents 封面頁
     證明書
     致謝詞
     論文摘要
     目錄
     圖目錄
     表目錄
     第一章 緒論
     第一節 研究背景與動機
     第二節 研究目的
     第三節 研究範圍與限制
     第四節 研究方法與步驟
     第五節 研究架構與流程
     第二章 文獻探討
     第一節 知識與知識管理
     第二節 資料庫與資料倉儲
     第三節 資料發掘與商業智慧
     第四節 網頁資料發掘
     第三章 研究方法
     第一節 研究架構
     第二節 研究方法
     第三節 研究流程
     第四節 研究步驟
     第四章 資料分析
     第一節 資料分析程序
     第二節 流量指標分析
     第三節 資源使用分析
     第四節 使用者活動分析
     第五章 結論與建議
     第一節 研究發現
     第二節 研究建議
     第三節 結論
     參考文獻		zh_TW
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#A2002001575en_US
dc.subject (關鍵詞) 資料發掘zh_TW
dc.subject (關鍵詞) 商業智慧zh_TW
dc.subject (關鍵詞) 網站經營者zh_TW
dc.subject (關鍵詞) 入口網站zh_TW
dc.subject (關鍵詞) 流量指標zh_TW
dc.title (題名) 網頁資料發掘技術導入網站經營者之研究－以入口網站之分類索引服務為例zh_TW
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) [1] 何光國，圖書資訊組織原理，三民書局，民國79年，頁25至26。
     [2] 吳琮璠、謝清佳，資訊管理 理論與實務，民國85年，頁1-10至1-12。
     [3] 邵敏華，建構開放性之企業知識管理系統，國立政治大學資訊管理研究所碩士論文，民國87年。
     [4] 馮國卿，知識管理在電子圖書館應用之研究，國立政治大學圖書資訊研究所碩士論文，民國87年。
     [5] 劉容志，IBM Software Update，民國87年10月。
     [6] 謝清俊，公共資訊系統概說，圖書館與資訊研究論文集，漢美書局，民國85年，頁163。
     [7] 樓玉玲，以資料發掘技術分析政大通識課程，國立政治大學資訊管理研究所碩士論文，民國87年。
     [8] 主題網際資訊，Visitor Relationship Management – WebTrends Enterprise Reporting Server，客戶關係管理研討會，民國89年五月。
     [9] Adriaans, P. and Zantinge, D., Data Mining, Addison-Wesley, 1996.
     [10] Bellinger, G., “Knowledge Management”, http://www.outsights.com/systems/kmgmt/kmgmt.htm
     [11] Berry, M. J. A. and Linoff, G., Data Mining Technique For Marketing, Sale, And Customer Support, Wiley Computer, 1997.
     [12] Cabena, P., Hadjinian, P., Stadler, R., Verhees, J., and Zanasi, A., Discovering Data Mining – From Concept to Implementation, Prentice Hall Ptr, 1998.
     [13] Codd, E. F., “Providing OLAP to User- Analysis: An IT Mandate”, Sep. 1998, http://www.arborsoft.com/essbase/wht_ppr/coodcl.html
     [14] Connelly, R., McNeill, R., and Mosimann, R., The Multi Dimensional Manager, Cognos, Oct. 1996.
     [15] Cooley, R., Mobasher, B., and Srivastava, J., “Data Preparation for Mining World Wide Web Browsing Patterns”, Knowledge and Information Systems, Vol. 1, No. 1, 1999.
     [16] Davis, M. C., “Knowledge Management”, Information Strategy: The Executive’s Journal, Fall 1998.
     [17] Harris, D.B., “Creating A Knowledge Centric Information Technology Environment”, Sep. 1998, http://www.htcs.com/ckc.html
     [18] Drucker, P. F., Post-Capitalist Society, Harper Collins, 1993, pp. 25-30.
     [19] Edvinsson, L. and Sullivan, P., “Developing a Model for Managing Intellectual Capital”, European Management Journal, Vol. 14. No. 4, Aug. 1996, pp. 356-364.
     [20] Fayyad, U. M., “Data Mining and Knowledge Discovery: Making Sense Out of Data”, IEEE Expert, Oct. 1996, pp. 20-25.
     [21] Fayyad, U. M. and Ramasamy, U., “Data Mining and Knowledge Discovery in Database”, Communications of The ACM, Nov. 1996, Vol. 39, pp. 24-26.
     [22] Frawley, W. J., Piatesky-Shapiro, and Matheus, G. C. J., Knowledge Discovery in Database: An Overview, AAAI/MIT Press, 1991, pp. 1-30.
     [23] Fuld, L. M., The New Competitor Intelligence: The Complete Resource for Finding, Analyzing, and Using Information about Your Competitors, NY: Wiley, 1995.
     [24] Gilad, B., The Art and Science of Business Intelligence Analysis: Business Intelligence Theory, Principles, Practices, and Uses”, ed. Gilad, B. and Herring, J. P., Jai Press Inc., 1996, p.4.
     [25] Gloede, C., “Designing A Business Intelligence System”, Midrange Systems, Dec. 12, 1997, pp. 49-50.
     [26] Greening, D. R., “Data Mining on the Web - There`s Gold in that Mountain of Data”, http://www.webtechniques.com/archives/2000/01/greening/
     [27] Grupe, F. H. and Owrang, M. M., “Data Base Mining Discovering New Knowledge and Cooperative Advantage,” Information Systems Management, Fall 1995, pp.26-31.
     [28] Hildebrand, C., “All Aboard the BI Bandwagon”, CIO, Vol.11, Jul. 15, 1998, p. 16.
     [29] IBM, “IBM Data Management White Paper - If data were money, would you manage it differently?”, 1999, http://www.software.ibm.com/data/busn-intel/biadinsert
     [30] Inmon, W. H., Building the Data Warehouse, Wellesley, MA:QED Technical Publishing Group, 1992.
     [31] Komenar, M., Electronic Marketing, Wiley Computer Publishing, 1993, pp.80-81.
     [32] Malhotra, Y., “World Wide Web Virtual Library on Knowledge Management”, Aug. 1998, http://www.brint.com/km/
     [33] Microsoft Sales Online!, Microsoft SQL Server Questions and Answers: “What is a data warehouse?”, Jan.1, 1997, http://www.microsoft.com/salesinfo/qa/mssq1013.html
     [34] Mobasher, B., Cooley, R., and Srivastava, J., “Web Mining: Information and Pattern Discovery on the World Wide Web”, http://www-users.cs.umn.edu/~mobasher/webminer/survey/survey.html
     [35] Nonaka, I., “The Knowledge Creating Company”, Harvard Business Review, Nov.-Dec., 1991, pp. 96-104.
     [36] Nonaka, I. and Takeuchi, H., The Knowledge Creating Company: How Japanese Companies Create the Dynamics of Innovation, Oxford University Express, 1995, p. 54.
     [37] OLAP Council, “OLAP and OLAP Server Definitions,” Sep. 1998, http://www.olapcouncil.org/research/
     [38] Paitetsky-Shapiro, G., Discovery, Analysis, and Presentation of Strong Rules”, Knowledge Discovery in Database, ed. G. Piatetsky-Shapiro and Frawley, W. J., CA: AAAI/MIT Press, 1991, pp. 229-238.
     [39] Shaw, R. and Stone, M., Database Marketing, Aldershot: Gwer Publishing, 1990.
     [40] Spek, R. van der and Spijkervet, A., “Knowledge Management: Dealing Intelligency with Knowledge”, Knowledge Management and Its Integrative Elements, ed. Liebowitz, J. and Wilcox, L. C. , NY: CRC Press, 1997, p. 40.
     [41] Vedder, R. G. and Vanecek, M. T., “Competitive Intelligence for IT Resource Planning: Some Lessons Learned”, Information Strategy: The Executive’s Journal, Fall 1998, pp. 29-36.
     [42] Wilson, R. F., “Web Marketing Today”, Jul. 1, 2000, http://www.wilsonweb.com/articles/bannerad.htm
     [43] Zanasi, A., “Competitive Intelligence through Data Mining Public Sources”, Competitive Intelligence Review, Vol. 9, 1998, pp. 44-54.		zh_TW