Carnegie Mellon University 
15-826: Multimedia Databases and Data Mining 
Fall 2011 - C. Faloutsos

Syllabus

DESCRIPTION

The course covers advanced algorithms for learning, analysis, data management and visualization of large datasets. 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, privacy and security issues, rule discovery, data visualization, graph mining, stream mining.

TOPICS TO BE COVERED

  1. Database topics:
  2. Tools:
  3. Data Mining:
  4. OVERVIEW OF RECENT TOPICS: trust and influence propagation; Future directions.
PREREQUISITES: Introductory database course  15-415 (familiarity with B-trees and Hashing), or permission of the instructor.

UNIVERSITY UNITS: 12

CORE UNITS: 1

TEXT

Copies of instructor's transparencies and notes, as well as copies of selected articles will be made available. The required text is Recommended, but not required texts:

METHOD OF EVALUATION

The course involves Clarifications:
Last updated: Sept. 2011, by Christos Faloutsos