15-829A Advanced Database Applications
Instructor: Christos Faloutsos
Description:
The course covers modern, cross-disciplinary applications of database systems. Topics include indexing for text and DNA databases, searching medical and multimedia databases by content, fundamental signal processing methods, compression, fractals in databases, data mining and rule discovery.

  1. ACCESS METHODS : Advanced hashing and multi-key access methods, indexing text and DNA strings, clustering, information filtering, singular value decomposition.
  2. MULTIMEDIA/MEDICAL DATABASES: Searching by content in signals: Time sequences, photographs and medical images, video clips; feature extraction; continuous media storage and delivery.
  3. FUNDAMENTAL SIGNAL PROCESSING METHODS: Discrete Fourier Transform, wavelets, JPEG and MPEG compression.
  4. FRACTALS IN DATABASES: Self-similarity/non-uniformity of real datasets, fractal dimensions, selectivity using fractals and multifractals; fractal image compression, self-similarity in web-traffic patterns.
  5. DATA MINING: Statistical methods, AI-methods, rule discovery in large databases, information compression and reconstruction.
  6. OVERVIEW OF RECENT TOPICS: Mobile databases; Data warehousing; Web databases; Future directions.

Prerequisites: Introductory database course (familiarity with B-trees and Hashing), or permission of the instructor.

Text:

Method of Evaluation:
The course involves

Each participant will make a 30 minute presentation to the rest of the class, covering about 3 research papers.

Projects will be carried out in teams of 1-3. A detailed handout about the project will be distributed at the beginning of the course, along with a list of suggested projects. The goal of the project is to give the participants the opportunity to tackle a large, interesting problem, which may lead to a publication.