1. Overviews of ITCS 6161/8161: Advanced Topics on Database Systems Dr. Jianping Fan Department of Computer Science UNC-Charlotte www.cs.uncc.edu/~jfan http://www.cs.uncc.edu/~jfan/itcs6161.html Course web site:

2. Course Web Site http://www.cs.uncc.edu/~jfan/itcs6161.html 1.Most useful information (course schedule, presentation slides, announcements, et al.) can be found and downloaded at: 2. You may check course web site before you come to classroom because this website will be updated frequently! 3. 10 hours/week rule: 2 hours for preparing, 2 hours for reviewing, 3 hours for class, & 3 hours for homework and projects

3. Course Information Class hour 9:25AM - 12:15PM, Friday Office hour Friday 14:00PM - 18:00PM Instructor - Dr. Jianping Fan email - jfan@uncc.edu Office – Woodward 205B Webpage http://www.cs.uncc.edu/~jfan Textbook: we will use the slices and papers on the course web page, but some good books are suggested on web site Classroom: Woodward Hall 135

4. What we have done in Database? Data modeling: data is structural and it can be modeled by E-R model! Data indexing: B-tree for one attribute! Query are well defined by SQL!

5. What we have done in Database? Database Information Retrieval

6. What we have done in Database? Information Retrieval Database Web Database Internet is changing everything!

7. What are Advanced Topics? Data Types are advanced rather than relational data! Data Analysis Tools are advanced rather than traditional ones! Applications are advanced rather than relational database!

8. How can I access web-scale data in database over Internet? Internet Course Objectives Data Server User Google, Yahoo! & MSN IE Big Data?

9. What are Advanced for such application? Data Types: Multi-Modal Data without structure! Data Analysis Tools: E-R model could be to simple! Applications: It is part of our daily life!

10. 1. How to store web-scale data? 2. How to analyze web-scale data ? 3. How to index web-scale data ? 4. How to access web-scale data in database? 5. How to control user’s access ? Course Content Problems we should address in this class: Web-scale data are always in multi-modals

11. Why we should have this course? Good job market: Google, Yahoo!.... Have fun: solving real problem Not so “hard” to learn (??) Next generation search engines

12. Tools to be Introduced a. Advanced Data Organization Tools; b. Advanced Data Analysis Tools; c.Machine Learning & Data Mining Tools for Knowledge Discovery from web-scale data collections. Internet is changing our life but ………

13. Database System Tools a.Data Representation Schema b.Database Indexing c.Database Storage d.Query Management

14. Data Analysis Tools a.Image & Video Analysis & Feature Extraction b.Object Detection & Scene Understanding c.Classifier Training for object and concept detection d. Scene Configuration and Structure

15. Knowledge Discovery Tools a.GMM & Bayesian Network b.Support Vector Machine (SVM) c.Graphical Models & Structure Learning d.Statistical Inference

16. Course Topics Data Mining Tools Machine Learning Tools Image/Video analysis and feature extraction Image/Video Database indexing Image/Video transmission over networks Query refinement for image/video retrieval Open discussion & topic-based student presentation What Yahoo!, Google are doing now

17. Grading Composition Project25% Show-up and understanding 10% Midterm30% Final35% Scale >93% = A 75-93% = B 55-74% = C <55% or cheating = F

18. Class Policy You have to attend the class and come to classroom on time (9:25am)! You should be ready to learn from the class You should respect your classmates: come to learn from their presentations!

19. Course Project Develop video analysis system using Visual C++ and Java. Each group consists 3-4 students 3-4 hours workload each week is expected Java or C++ assumed Research Presentation Project Video Analysis Project More information http://www.cs.uncc.edu/~jfan/itcs6161.html

20. Midterm & Final Tests closed books and notes One page notes is permitted Cumulative No makeup Bonus is expected

21. Suggestions from Instructor Do your best in the class Show your problems to the instructor when you cannot make it Show the evidence to us if you think you are right. Open discussion is welcome

22. Who cares? Google Search Engine

23. Who cares?

24. Google & Yahoo!

25. Who cares? You & Your Start-ups

26. The way to join them Good grade from class More training on programming skills, especially for multimedia analysis, indexing and retrieval Get recommendation from professor

27. Recommendation Good grade is very important, but it is not everything! Learning something and solving one problem you like may be more important! Learning from someone who may make you better! Especially your classmates

28. Research areas we will touch Computer Vision Database & Data Mining Information Retrieval Machine Learning & AI Visualization Networks Statistics & Security

29. Q & A

30. If these are too hard for you, you still have chance to withdraw now! You have chance!