Data Mining
Course Information
Instructors: Anand Rajaraman (anand @ cs dt stanford dt edu), Jeffrey D. Ullman (ullman @ gmail dt com).
Materials: There is no text, but students will use the Gradiance automated homework system for which a nominal fee will be charged. Notes and/or slides will be posted on-line. You can see earlier versions of the notes and slides covering Data Mining. Not all these topics will be covered this year.
Requirements: There will be periodic homeworks (some on-line, using the Gradiance system), a final exam, and a project on web-mining, using the Stanford WebBase. The homework will count just enough to encourage you to do it, about 20%. The project and final will account for the bulk of the credit, in roughly equal proportions.
Click Here To Download PDF Notes-
Course Information
Instructors: Anand Rajaraman (anand @ cs dt stanford dt edu), Jeffrey D. Ullman (ullman @ gmail dt com).
Materials: There is no text, but students will use the Gradiance automated homework system for which a nominal fee will be charged. Notes and/or slides will be posted on-line. You can see earlier versions of the notes and slides covering Data Mining. Not all these topics will be covered this year.
Requirements: There will be periodic homeworks (some on-line, using the Gradiance system), a final exam, and a project on web-mining, using the Stanford WebBase. The homework will count just enough to encourage you to do it, about 20%. The project and final will account for the bulk of the credit, in roughly equal proportions.
Click Here To Download PDF Notes-
Handouts
Note: The slides labeled as "for Anand's lecture" are authored by Anand Rajaraman.- Introduction to Data Mining Powerpoint Slides for Jeff's half of 9/26 lecture. [PDF]
- Introduction to Web Mining Powerpoint Slides for Anand's half of 9/26 lecture and part of 9/28 lecture. [PDF]
- Mining Frequent Pairs; A-Priori Powerpoint Slides for Jeff's 9/28 lecture. [PDF]
- Improved Methods for Frequent-Pair Mining Powerpoint Slides for Jeff's 10/3 lecture. [PDF]
- Web Crawling Powerpoint slides for Anand's 10/5 lecture. [PDF]
- PageRank and Hubs/Authorities Powerpoint Slides for Jeff's 10/10 and 10/12 lectures. [PDF]
- Minhashing and Locality-Sensitive Hashing Powerpoint Slides for Jeff's 10/12 and 10/17 lectures. [PDF]
- Topic-Specific PageRank Powerpoint Slides for Anand's 10/19 lecture. [PDF]
- Web Spam Powerpoint Slides for Anand's 10/24 lecture. [PDF]
- Introduction to Stream Mining Powerpoint Slides for Jeff's 10/26 lecture. [PDF]
- Stream Mining, Estimating Frequencies Powerpoint Slides - Set #1 and Powerpoint Slides - Set #2 for Jeff's 10/31 and 11/2 lectures. [PDF] [PDF]
- Extracting Relational Data from the Web Powerpoint Slides for Anand's 11/07 lecture. [PDF]
- Virtual Databases Powerpoint Slides - Set #1 and Powerpoint Slides - Set #2 for Anand's 11/09 lecture. [PDF] [PDF]
- Introduction to Clustering, k-Means Powerpoint Slides for Jeff's 11/14 and 11/16 lectures. [PDF]
- More on Clustering Powerpoint Slides for Jeff's 11/28 lecture. [PDF]
- Optimizing Selection of Ads Powerpoint Slides for Anand's 11/30 lecture. [PDF]
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