Overviews of ITCS 6161/8161: Advanced Topics on Database Systems

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

• Most useful information (course schedule,
• presentation slides, announcements, et al.)
• can be found and downloaded at

http//www.cs.uncc.edu/jfan/itcs6161.html
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
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Course Information

• Class hour 925AM - 1215PM, Friday
• Office hour Friday 1400PM - 1800PM
• Instructor - Dr. Jianping Fan
• email - jfan_at_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

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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!

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

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Course Objectives
Google, Yahoo! MSN IE
Big Data?

How can I access web-scale data in database over
Internet?
Internet
User
Data Server
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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!

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Course Content
Problems we should address in this class
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 users access ?
Web-scale data are always in multi-modals
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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

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Tools to be Introduced

• a. Advanced Data Organization Tools
• b. Advanced Data Analysis Tools
• Machine Learning Data Mining Tools for
• Knowledge Discovery from web-scale data
  collections.

Internet is changing our life but
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Database System Tools

1. Data Representation Schema
2. Database Indexing
3. Database Storage
4. Query Management

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Data Analysis Tools

• Image Video Analysis Feature Extraction
• Object Detection Scene Understanding
• Classifier Training for object and concept
• detection
• d. Scene Configuration and Structure

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Knowledge Discovery Tools

1. GMM Bayesian Network
2. Support Vector Machine (SVM)
3. Graphical Models Structure Learning
4. Statistical Inference

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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

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Grading

• Composition
• Project 25
• Show-up and understanding 10
• Midterm 30
• Final 35
• Scale
• gt93 A
• 75-93 B
• 55-74 C
• lt55 or cheating F

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Class Policy

• You have to attend the class and come to
  classroom on time (925am)!
• You should be ready to learn from the class
• You should respect your classmates come to learn
  from their presentations!

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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

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Midterm Final Tests

• closed books and notes
• One page notes is permitted
• Cumulative
• No makeup
• Bonus is expected

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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

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Who cares?
Google Search Engine

• Google Search Engine

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Who cares?
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Who cares?
Google Yahoo!
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Who cares?
You Your Start-ups
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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

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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

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Research areas we will touch

• Computer Vision
• Database Data Mining
• Information Retrieval
• Machine Learning AI
• Visualization
• Networks
• Statistics Security

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