Key: ppt = powerpoint, pdf
= pdf optimized for presentation, pdf
= pdf optimized for printing, src = latex source of pdf
| powerpoint | latex | ||||
| 01 | Boolean retrieval |
ppt1
ppt2
pdf |
pdf |
pdf |
src |
| 02 | The term vocabulary & postings lists |
ppt1
ppt2
pdf |
pdf |
pdf |
src |
| 03 | Dictionaries and tolerant retrieval |
ppt1
ppt2
pdf |
pdf |
pdf |
src |
| 04 | Index construction |
ppt1
ppt2
pdf |
pdf |
pdf |
src |
| 05 | Index compression |
ppt1
ppt2
pdf |
pdf |
pdf |
src |
| 06 | Scoring, term weighting & the vector space model |
ppt1
ppt2
pdf |
pdf |
pdf |
src |
| 07 | Computing scores in a complete search system |
ppt1
ppt2
pdf |
pdf |
pdf |
src |
| 08 | Evaluation in information retrieval |
ppt1
ppt2
pdf |
pdf |
pdf |
src |
| 09 | Relevance feedback & query expansion |
ppt1
ppt2
pdf |
pdf |
pdf |
src |
| 10 | XML retrieval | (old) ppt2 |
pdf |
pdf |
src |
| 11 | Probabilistic information retrieval | (old) ppt2 |
pdf |
pdf |
src |
| 12 | Language models for information retrieval | (old) ppt2 |
pdf |
pdf |
src |
| 13 | Text classification & Naive Bayes |
ppt1
ppt2
pdf |
pdf |
pdf |
src |
| 14 | Vector space classification |
ppt1
ppt2
pdf |
pdf |
pdf |
src |
| 15-1 | Support vector machines |
ppt1
ppt2
pdf |
pdf |
pdf |
src |
| 15-2 | Learning to rank |
ppt1
ppt2
pdf |
pdf |
pdf |
src |
| 16 | Flat clustering |
ppt1
ppt2
pdf |
pdf |
pdf |
src |
| 17 | Hierarchical clustering |
ppt1
ppt2
pdf |
pdf |
pdf |
src |
| 18 | Matrix decompositions & latent semantic indexing |
ppt1
ppt2
pdf |
pdf |
pdf |
src |
| 19 | Web search basics |
ppt1
ppt2
pdf |
pdf |
pdf |
src |
| 20 | Web crawling and indexes |
ppt1
ppt2
pdf |
pdf |
pdf |
src |
| 21 | Link analysis |
ppt1
ppt2
pdf |
pdf |
pdf |
src |
Slides have also been published by a number of other instructors who are using the book, e.g., by Jim Martin, Donald Patterson Min-Yen Kan, and Zhang & Helmer.