Key: pdf/1 = one slide per page, pdf/6 = 6 slides per page, pdf/present = pdf optimized for presentation, pdf/print = pdf optimized for printing, source = latex source of pdf
| powerpoint | latex | ||
| 01 | Boolean retrieval | ppt pdf/1 pdf/6 | pdf/present pdf/print source |
| 02 | The term vocabulary & postings lists | ppt pdf/1 pdf/6 | pdf/present pdf/print source |
| 03 | Dictionaries and tolerant retrieval | ppt pdf/1 pdf/6 | pdf/present pdf/print source |
| 04 | Index construction | ppt pdf/1 pdf/6 | pdf/present pdf/print source |
| 05 | Index compression | ppt pdf/1 pdf/6 | pdf/present pdf/print source |
| 06 | Scoring, term weighting & the vector space model | ppt pdf/1 pdf/6 | pdf/present pdf/print source |
| 07 | Computing scores in a complete search system | ppt pdf/1 pdf/6 | pdf/present pdf/print source |
| 08 | Evaluation in information retrieval | ppt pdf/1 pdf/6 | pdf/present pdf/print source |
| 09 | Relevance feedback & query expansion | ppt pdf/1 pdf/6 | pdf/present pdf/print source |
| 10 | XML retrieval | old slides | |
| 11 | Probabilistic information retrieval | old slides | |
| 12 | Language models for information retrieval | old slides | |
| 13 | Text classification & Naive Bayes | ppt pdf/1 pdf/6 | pdf/present pdf/print source |
| 14 | Vector space classification | ppt pdf/1 pdf/6 | pdf/present pdf/print source |
| 15 | Support vector machines & machine learning on documents | ppt pdf/1 pdf/6 | |
| 16 | Flat clustering | ppt pdf/1 pdf/6 | pdf/present pdf/print source |
| 17 | Hierarchical clustering | ppt pdf/1 pdf/6 | pdf/present pdf/print source |
| 18 | Matrix decompositions & latent semantic indexing | ppt pdf/1 pdf/6 | |
| 19 | Web search basics | ppt pdf/1 pdf/6 | pdf/present pdf/print source |
| 20 | Web crawling and indexes | ppt pdf/1 pdf/6 | pdf/present pdf/print source |
| 21 | Link analysis | ppt pdf/1 pdf/6 | pdf/present pdf/print source |
Slides have also been published by a number of other instructors who are using the book, e.g., by Jim Martin, Donald Patterson and Min-Yen Kan.