Carnegie Mellon University
15-826 Multimedia Databases and Data Mining
Spring 2005 - C. Faloutsos

Lecture foils




Lecture date Foils Topic
1/11 010_intro-db.pdf overview of relational and OR-DBMS
1/11 020_b-trees.pdf primary key indexing: b-trees
1/18 030_hashing.pdf                                  :hashing (static and extendible)
1/18 110_SAMs1.pdf multi-key and spatial access methods - part I
1/20 120_SAMs2.pdf spatial access methods: z-ordering 
1/25-27 130_SAMs3.pdf                                    : R-trees 
2/1 140_SAMs4.pdf                                     : grid files, dim. curse
2/1 150_SAMs5.pdf                                     : metric trees, nn search algorithms
2/3-8 160_fractals1.pdf fractals: introduction (fd, multifractals, fat fractals, power laws)
2/10 170_fractals2.pdf            : case studies - part-I (r-tree performance; dim. reduction)
2/10 180_fractals3.pdf            : case studies - part-II (dim. curse, M-trees analysis)
2/15 190_fractals4.pdf            : case studies - part III (regions, quadtrees)
2/17 210_text1.pdf text    : full text scanning
2/17 220_text2.pdf text    : part-II: inversion; signature files
2/24 230_text3.pdf text    : part-III: clustering
2/24 240_text4.pdf text    : part-IV: LSI
2/28 Foils by C. Olston  Web searching and mining
3/3 250_SVD1.pdf SVD  : part-I: definitions
3/15 260_SVD2.pdf           : part-II: case studies
3/15 270_SVD3.pdf           : part-III: properties and case studies
3/17 310_multimediaDB.pdf multimedia indexing (time series, images, FastMap)
3/22 320_DSP.pdf DSP tools: Fourier and wavelets 
3/24
330_JPEG.pdf compression: JPEG, MPEG and fractal
4/5
410_GraphMining.pdf Graph Mining: Laws, generators, virus propagation
4/7
Foils by Prof. Ziv Bar-Joseph
Data Mining in Bioinformatics
3/29 430_TimeSeriesForecasting.pdf Time Series: sensor mining and forecasting
4/1
510_DM-stat.pdf Data Mining: Statistics basics
4/1 520_DM-AI.pdf Data Mining: AI basics 
4/1
530_DM-OLAP.pdf Data Mining: OLAP and Data Warehousing
4/12
540_DM-Trees+Rules.pdf Data Mining: DB concepts - trees and association rules
4/19
550_DM-clustering.pdf Data Mining: DB concepts - clustering
4/21
610_LOCI.pdf Spatial DM: outliers
4/21
620_ICA.pdf Temporal DM: ICA
4/21
630_linreg.pdf Information recovery - linear regularization (updated 4/25)
4/25
640_appxCountingPalmer.pdf
Approximate Counting
4/25
700_Conclusions.pdf
Overall conclusions


Updated by christos <at> cs.cmu.edu, 4/25/2005.