Course Information
Instructors: Anand Rajaraman (anand @ kosmix dt com), Jeffrey D. Ullman (ullman @ gmail dt com).
Lecture notes in ppt and pdf formats for download .
| Topic | PowerPoint Slides | PDF Document |
| 1. Introductory Remarks (JDU) | ||
| 2. Introductory Remarks (AR) | ||
| 3. Map-Reduce | ||
| 4. Frequent Itemsets 1 | ||
| 5. Frequent Itemsets 2 | ||
| 6. Peter Pawlowski's Talk on Aster Data | ||
| 7. Nanda Kishore's Talk on ShareThis | ||
| 8. Recommendation Systems | ||
| 9. Shingling, Minhashing, Locality-Sensitive Hashing | ||
| 10. Applications and Variants of LSH | ||
| 11. Distance Measures, Generalizations of Minhashing and LSH | ||
| 12. High-Similarity Algorithms | ||
| 13. PageRank | ||
| 14. Link Spam, Hubs & Authorities | ||
| 15. Generalization of Map-Reduce | ||
| 16. Clustering | ||
| 17. Streaming Data | ||
| 18. Relation Extraction | ||
| 19. On-Line Algorithms, Advertising Optimization | ||
| 20. Algorithms on Streams |
