The following is a preliminary schedule for CS 5083 Knowledge Discovery and Data Mining. This schedule will be updated as the semester progresses. Also, although it is not listed on each day, there will be project discussions every class period.
| Date | Topic | Due |
| Jan 20 (Week 1) | What is data mining? Seminar style classes, project discussion | |
| Jan 22 | Is data mining just statistics? Project discussion |
Project ideas |
| Jan 27 (Week 2) | Snow day! | |
| Jan 29 | Fast Algorithms for Mining Association Rules (if link does not work, paper is also on D2L) | Summary 1, Vote on Project |
| Feb 3 (Week 3) | Statewide Monitoring of the Mesoscale Environment: A Technical Update on the Oklahoma Mesonet (paper on D2L) | Summary 2 |
| Feb 5 | A Geographic Information Systems?Based Analysis of Supercells across Oklahoma from 1994 to 2003 (paper on D2L) | Summary 3 |
| Feb 10 (Week 4) | Catch up on the GIS paper and project discussion | |
| Feb 12 | Very Simple Classification Rules Perform Well on Most Commonly Used Datasets | Summary 4 |
| Feb 17 (Week 5) | Random Forests | Summary 5 |
| Feb 19 | Exploiting Relational Structure to Understand Publication Patterns in High-Energy Physics | Summary 6 |
| Feb 24 (Week 6) | Handling Missing Features when Applying Classification Models | Summary 7 |
| Feb 26 | Constrained K-means Clustering with Background Knowledge | Summary 8 |
| Mar 3 (Week 7) | Clustering Distributed Time Series in Sensor Networks | Summary 9 |
| Mar 5 | Pick a Keogh paper | Summary 10 |
| Mar 10 (Week 8) | iSAX: Indexing and Mining Terabyte Sized Time Series. Additional information is here. | Summary 11 |
| Mar 12 | ||
| Mar 14-22 | Spring Break! |
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| Mar 24 (Week 9) | A tutorial on Principal Component Analysis | Summary 12 |
| Mar 26 | Can Complex Network Metrics Predict the Behavior of NBA Teams? paper is also on D2L if the above doesn't work. | Summary 13 |
| Mar 31 (Week 10) | Predicting Future Decision Trees from Evolving Data (paper on D2L) | Summary 14 |
| Apr 2 | The NFL Coaching Network: Analysis of the Social Network Among Professional Football Coaches | Summary 15 |
| Apr 7 (Week 11) | Project discussion (Dr Basara leading class) | |
| Apr 9 | Temporal-Relational Classifiers for Prediction in Evolving Domains | Summary 16 |
| Apr 14 (Week 12) | Learning Relational Probability Trees | Summary 17 |
| Apr 16 | Spatiotemporal Relational Probability Trees | Summary 18 |
| Apr 21 (Week 13) | Learn all you can about PageRank. | Summary 19 |
| Apr 23 | Joke Retrieval: Recognizing the Same Joke Told Differently | Summary 20 |
| Apr 28 (Week 14) | Finding Text Reuse on the Web | Summary 21 |
| Apr 30 | C4. 5, class imbalance, and cost sensitivity: why under-sampling beats over-sampling | Summary 22 |
| May 5 (Week 15) | Project work | |
| May 7 | Presentations at NWC 3902 | |
| May 15 | No final! |
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