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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。\r\n[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。\r\n[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。\r\n[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。\r\n[5] 劉容志，IBM Software Update，民國87年10月。\r\n[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。\r\n[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。\r\n[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。\r\n[9] Adriaans, P. and Zantinge, D., Data Mining, Addison-Wesley, 1996.\r\n[10] Bellinger, G., “Knowledge Management”, http://www.outsights.com/systems/kmgmt/kmgmt.htm\r\n[11] Berry, M. J. A. and Linoff, G., Data Mining Technique For Marketing, Sale, And Customer Support, Wiley Computer, 1997.\r\n[12] Cabena, P., Hadjinian, P., Stadler, R., Verhees, J., and Zanasi, A., Discovering Data Mining – From Concept to Implementation, Prentice Hall Ptr, 1998.\r\n[13] Codd, E. F., “Providing OLAP to User- Analysis: An IT Mandate”, Sep. 1998, http://www.arborsoft.com/essbase/wht_ppr/coodcl.html\r\n[14] Connelly, R., McNeill, R., and Mosimann, R., The Multi Dimensional Manager, Cognos, Oct. 1996.\r\n[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.\r\n[16] Davis, M. C., “Knowledge Management”, Information Strategy: The Executive’s Journal, Fall 1998.\r\n[17] Harris, D.B., “Creating A Knowledge Centric Information Technology Environment”, Sep. 1998, http://www.htcs.com/ckc.html\r\n[18] Drucker, P. F., Post-Capitalist Society, Harper Collins, 1993, pp. 25-30.\r\n[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.\r\n[20] Fayyad, U. M., “Data Mining and Knowledge Discovery: Making Sense Out of Data”, IEEE Expert, Oct. 1996, pp. 20-25.\r\n[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.\r\n[22] Frawley, W. J., Piatesky-Shapiro, and Matheus, G. C. J., Knowledge Discovery in Database: An Overview, AAAI/MIT Press, 1991, pp. 1-30.\r\n[23] Fuld, L. M., The New Competitor Intelligence: The Complete Resource for Finding, Analyzing, and Using Information about Your Competitors, NY: Wiley, 1995.\r\n[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.\r\n[25] Gloede, C., “Designing A Business Intelligence System”, Midrange Systems, Dec. 12, 1997, pp. 49-50.\r\n[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/\r\n[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.\r\n[28] Hildebrand, C., “All Aboard the BI Bandwagon”, CIO, Vol.11, Jul. 15, 1998, p. 16.\r\n[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\r\n[30] Inmon, W. H., Building the Data Warehouse, Wellesley, MA:QED Technical Publishing Group, 1992.\r\n[31] Komenar, M., Electronic Marketing, Wiley Computer Publishing, 1993, pp.80-81.\r\n[32] Malhotra, Y., “World Wide Web Virtual Library on Knowledge Management”, Aug. 1998, http://www.brint.com/km/\r\n[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\r\n[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\r\n[35] Nonaka, I., “The Knowledge Creating Company”, Harvard Business Review, Nov.-Dec., 1991, pp. 96-104.\r\n[36] Nonaka, I. and Takeuchi, H., The Knowledge Creating Company: How Japanese Companies Create the Dynamics of Innovation, Oxford University Express, 1995, p. 54.\r\n[37] OLAP Council, “OLAP and OLAP Server Definitions,” Sep. 1998, http://www.olapcouncil.org/research/\r\n[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.\r\n[39] Shaw, R. and Stone, M., Database Marketing, Aldershot: Gwer Publishing, 1990.\r\n[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.\r\n[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.\r\n[42] Wilson, R. F., “Web Marketing Today”, Jul. 1, 2000, http://www.wilsonweb.com/articles/bannerad.htm\r\n[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) https://ah.lib.nccu.edu.tw/item?item_id=95017-
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\r\n證明書\r\n致謝詞\r\n論文摘要\r\n目錄\r\n圖目錄\r\n表目錄\r\n第一章 緒論\r\n第一節 研究背景與動機\r\n第二節 研究目的\r\n第三節 研究範圍與限制\r\n第四節 研究方法與步驟\r\n第五節 研究架構與流程\r\n第二章 文獻探討\r\n第一節 知識與知識管理\r\n第二節 資料庫與資料倉儲\r\n第三節 資料發掘與商業智慧\r\n第四節 網頁資料發掘\r\n第三章 研究方法\r\n第一節 研究架構\r\n第二節 研究方法\r\n第三節 研究流程\r\n第四節 研究步驟\r\n第四章 資料分析\r\n第一節 資料分析程序\r\n第二節 流量指標分析\r\n第三節 資源使用分析\r\n第四節 使用者活動分析\r\n第五章 結論與建議\r\n第一節 研究發現\r\n第二節 研究建議\r\n第三節 結論\r\n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。\r\n[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。\r\n[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。\r\n[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。\r\n[5] 劉容志，IBM Software Update，民國87年10月。\r\n[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。\r\n[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。\r\n[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。\r\n[9] Adriaans, P. and Zantinge, D., Data Mining, Addison-Wesley, 1996.\r\n[10] Bellinger, G., “Knowledge Management”, http://www.outsights.com/systems/kmgmt/kmgmt.htm\r\n[11] Berry, M. J. A. and Linoff, G., Data Mining Technique For Marketing, Sale, And Customer Support, Wiley Computer, 1997.\r\n[12] Cabena, P., Hadjinian, P., Stadler, R., Verhees, J., and Zanasi, A., Discovering Data Mining – From Concept to Implementation, Prentice Hall Ptr, 1998.\r\n[13] Codd, E. F., “Providing OLAP to User- Analysis: An IT Mandate”, Sep. 1998, http://www.arborsoft.com/essbase/wht_ppr/coodcl.html\r\n[14] Connelly, R., McNeill, R., and Mosimann, R., The Multi Dimensional Manager, Cognos, Oct. 1996.\r\n[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.\r\n[16] Davis, M. C., “Knowledge Management”, Information Strategy: The Executive’s Journal, Fall 1998.\r\n[17] Harris, D.B., “Creating A Knowledge Centric Information Technology Environment”, Sep. 1998, http://www.htcs.com/ckc.html\r\n[18] Drucker, P. F., Post-Capitalist Society, Harper Collins, 1993, pp. 25-30.\r\n[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.\r\n[20] Fayyad, U. M., “Data Mining and Knowledge Discovery: Making Sense Out of Data”, IEEE Expert, Oct. 1996, pp. 20-25.\r\n[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.\r\n[22] Frawley, W. J., Piatesky-Shapiro, and Matheus, G. C. J., Knowledge Discovery in Database: An Overview, AAAI/MIT Press, 1991, pp. 1-30.\r\n[23] Fuld, L. M., The New Competitor Intelligence: The Complete Resource for Finding, Analyzing, and Using Information about Your Competitors, NY: Wiley, 1995.\r\n[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.\r\n[25] Gloede, C., “Designing A Business Intelligence System”, Midrange Systems, Dec. 12, 1997, pp. 49-50.\r\n[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/\r\n[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.\r\n[28] Hildebrand, C., “All Aboard the BI Bandwagon”, CIO, Vol.11, Jul. 15, 1998, p. 16.\r\n[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\r\n[30] Inmon, W. H., Building the Data Warehouse, Wellesley, MA:QED Technical Publishing Group, 1992.\r\n[31] Komenar, M., Electronic Marketing, Wiley Computer Publishing, 1993, pp.80-81.\r\n[32] Malhotra, Y., “World Wide Web Virtual Library on Knowledge Management”, Aug. 1998, http://www.brint.com/km/\r\n[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\r\n[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\r\n[35] Nonaka, I., “The Knowledge Creating Company”, Harvard Business Review, Nov.-Dec., 1991, pp. 96-104.\r\n[36] Nonaka, I. and Takeuchi, H., The Knowledge Creating Company: How Japanese Companies Create the Dynamics of Innovation, Oxford University Express, 1995, p. 54.\r\n[37] OLAP Council, “OLAP and OLAP Server Definitions,” Sep. 1998, http://www.olapcouncil.org/research/\r\n[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.\r\n[39] Shaw, R. and Stone, M., Database Marketing, Aldershot: Gwer Publishing, 1990.\r\n[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.\r\n[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.\r\n[42] Wilson, R. F., “Web Marketing Today”, Jul. 1, 2000, http://www.wilsonweb.com/articles/bannerad.htm\r\n[43] Zanasi, A., “Competitive Intelligence through Data Mining Public Sources”, Competitive Intelligence Review, Vol. 9, 1998, pp. 44-54.zh_TW