1 / 17

Advanced Database System Design

Advanced Database System Design. Instructor: Ruoming Jin Fall 2010. Welcome!. Instructor: Ruoming Jin Homepage: www.cs.kent.edu/~jin/ Office: 264 MCS Building Email: jin@cs.kent.edu Office hour: Tuesday (5:00PM-5:30PM) Thursdays (4:30PM to 5:30PM) or by appointment. Overview.

benjamin-morton
Download Presentation

Advanced Database System Design

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Advanced Database System Design Instructor: Ruoming Jin Fall 2010

  2. Welcome! • Instructor: Ruoming Jin • Homepage: www.cs.kent.edu/~jin/ • Office: 264 MCS Building • Email: jin@cs.kent.edu • Office hour: Tuesday (5:00PM-5:30PM) Thursdays (4:30PM to 5:30PM) or by appointment

  3. Overview • Homepage: www.cs.kent.edu/~jin/AdvDB10Fall/datamining.html • Time: 5:30-6:45PM Tuesdays and Thursdays • Place: MSB 228 • Prerequisite: Into to Database, Data Structures, and Algorithms.

  4. Overview • No Official Textbook • References Hector Garcia-Molia, Jeffrey Ullman, and Jennifer Widom, Database Systems, The Complete Book, Prentice Hall, 2002  Silberschatz, Korth, Sudarshan, Database System Concepts, 5th Edition, McGraw Hill 2006         Bin Liu, Web Data Mining, Springer, 2007 Ricardo Baeza-Yates and Berthier Riberiro-Neto, Modern Information Retrieval, Addison Wesley, 1999 Ian H. Witten, Alistair Moffat, and Timothy Bell, Managing Gigabytes, Second Edition, Morgan Kaufmann, 1999

  5. Overview • Grading scheme • No exam

  6. Overview (Presentation) • Paper presentation • One per student • Research paper(s) • List of recommendations (will be available by the end of Sept.) • Your own pick (upon approval) • Your overall presentation will be less than 40 minutes (30 minutes talk) • Three parts • Review of research ideas in the paper • Debate (Pros/Cons) • Questions and comments from audience

  7. Overview (Presentation) • Order of presentation: assigned by instructor • The presentation will start from late October or early November • You need submit two drafts before the final presentation • First draft due on Oct. 14th • Second draft due on Oct. 21th • Final slides due one day before your presentation. • I will provide feedback and suggestion for each draft • Note that I do expect the complete presentation slides in the first draft

  8. Overview (Project) • Project (due Dec 7rd) • One project: One to Three students (The more students, the more task is expected to be done). • Some basic suggestion later. • A variety of subjects (some of them has individual mentors). • Checkpoints • Proposal: title and goal (due Sep. 30th) • Outline of approach (due Oct 7th) • An intermediate report and research discussion (Nov. 3rd) • Project/Demo Presentation (Dec 9th) • Documentation (due Dec 14rd) • Each group will have a short presentation and demo (20 minutes) • Each group will provide a five-page document on the project

  9. Topics 1 • Scope: Data Warehouse/Data Mining • Topics: • OLAP • Association Rule • Classification and Prediction • Clustering

  10. Topics 2 • Scope: Web Mining/Information Extraction • Topics: • Web Crawler • Page Rank • Text Mining (basics) • Information Extraction (basics)

  11. Topics 3 • Scope: Relational DB Implementation • Topics: • Query Evaluation • Query Optimization • Indexing

  12. Topics 4 • Scope: Information Retrieval • Topics: • Inverted List • Query Evaluation • Index Construction/Compression

  13. Presentation Topics • Social Network Analysis • New Database Architecture • Cloud Computing • Information Integration

  14. Project Ideas • Web Mining + Social Network Analysis • Twitter, Wikipedia • Fatwallet • Eopinion/Amazon • Yelp • Computer Science Literature • Information/Data Integration • Noaa data • Mobile Data Mining • Mobile user profiling

  15. Schedule Discussion

  16. Introduce Yourself!

  17. Questions and Thoughts!

More Related