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Data Mining

Data Mining. 第八組 B88901079 萬佳育 B88901132 葉書蘋. Outline. Why Data Mining What is Data Mining Data Mining Algorithm Applications. Data Mining 之價值. Times 時代雜誌 預估: “Data Mining 將是 21世紀 最熱門之五大新興行業“ 麻省理工學院 2000 年 元月號 ” 科技評論 ” (Technology Review) 預測 :

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Data Mining

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  1. Data Mining 第八組 B88901079 萬佳育 B88901132 葉書蘋

  2. Outline • Why Data Mining • What is Data Mining • Data Mining Algorithm • Applications

  3. Data Mining 之價值 • Times時代雜誌預估: “Data Mining將是 21世紀最熱門之五大新興行業“ • 麻省理工學院2000年 元月號”科技評論” (Technology Review) 預測: “未來會改變世界的十大新興科技中: Data Mining 名列前矛“ • IDC 於 2002年3月預測 “Data Mining 市場未來5年將大幅成長 將於短短四年成長 200%”

  4. Why Data Mining？ • 何謂資料庫？ • 資料量大增 • 全世界資料庫的資料量每20個月就增加一倍！

  5. Web data Data warehousing CRM systems Operational data Why Data Mining? (cont.) • 資料雖多，了解卻少 • We are drowning in data, but starving for knowledge! • Solution • Data Mining

  6. What Is Data Mining? • 資料採礦???? • “Data mining is the process of exploration and analysis, by automatic or semi-automatic means, of large quantities of data in order to discover meaningful patterns and rules.” • Mastering Data Mining by M. Berry/ G. Linoff--

  7. What Is Data Mining? • 在一大群資料中找出pattern，賦予原本雜亂無章的資料意義，進而從中歸納出理論 • 挖出金礦！！！

  8. From Data to Knowledge

  9. IQ=High IQ=Low Attend College: 79% Yes 11% No Attend College: 45% Yes 55% No Wealth = False Parents Encourage = Yes Parents Encourage = No Wealth = True Attend College: 70% Yes 30% No Attend College: 31% Yes 69% No Attend College: 94% Yes 6% No Attend College: 69% Yes 21% No The deciding factors for high school students to attend college are… All Students Attend College: 55% Yes 45% No IQ ? Wealth Parents Encourage?

  10. Data To Predict Training Data Mining Model Mining Model Mining Model Predicted Data Data Mining的程序 DM Engine DM Engine

  11. Data Mining 的工作循環

  12. Customer Profiling • 找出客戶共同特徵，以預測可能成為客戶的人 • 可降低成本，提高行銷的成功率。

  13. Data Mining Algorithm • Classification learning • Association learning • Clustering • Numeric prediction

  14. Inferring rudimentary rules

  15. Statistical modeling

  16. Amazon

  17. Amazon

  18. Amazon

  19. Amazon

  20. e-Oscar

  21. e-Oscar • 支持某網站的族群同時也支持的其它網站 • 有那些不同種類的網站，分享著相同的網友族群。

  22. e-Oscar • 替網站建立關聯性 --------------有效決定廣告策略 • 瞭解網友上網習性 ------------提供給管理者建構 個人化網站的資訊

  23. Software • MLC++ (pd) • MOBAL (pd) • MOBAL (pd) • Emerald (rp) • Kepler (rp) • Clementine (cp) • DataMind DataCruncher (cp) • Darwin (cp) • Intelligent Miner (cp) • INSPECT (cp) • NeoVista Solutions (cp) • Nuggets (cp) • Partek (cp) • Polyanalyst (cp) • SAS Data Mining (cp) • Statiatica • SGI MindSet (cp) • Knowledge Explorer (cp) • DataEngine (cp) • Delta Miner (cp) • S-PLUS (cp) • MATLAB (cp) • Mathematica (cp) • XGOBI (pd) • Crystal Vision neé ExplorN • sphinxVision • Graf-FX • IRIS • Spotfire • Netmap • Visible Decisions Inc. • Visual Mine

  24. Reference • Data Mining：Practical Machine Learning Tools and Techniques with Java Implementations/Ian H. Written, Eibe Frank/The Morgan Kaufmann/October 1999 • http://www.datamining.org.tw • http://www.twocrows.com/glossary.htm • http://www.mkp.com/ • http://www.uniminer.com/center01.htm • http://www.amazon.com

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