Introduction to Information Retrieval: Slides
Powerpoint slides are from the Stanford CS276 class and from the Stuttgart IIR class. Latex slides are from the Stuttgart IIR class. The latex slides are in latex beamer, so you need to know/learn latex to be able to modify them. You will need these beamer style files.
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| 01 | Boolean retrieval | ppt1 ppt2 pdf pdf | pdf | pdf | src |
| 02 | The term vocabulary & postings lists | ppt1 ppt2 pdf pdf | pdf | pdf | src |
| 03 | Dictionaries and tolerant retrieval | ppt1 ppt2 pdf pdf | pdf | pdf | src |
| 04 | Index construction | ppt1 ppt2 pdf pdf | pdf | pdf | src |
| 05 | Index compression | ppt1 ppt2 pdf pdf | pdf | pdf | src |
| 06 | Scoring, term weighting & the vector space model | ppt1 ppt2 pdf pdf | pdf | pdf | src |
| 07 | Computing scores in a complete search system | ppt1 ppt2 pdf pdf | pdf | pdf | src |
| 08 | Evaluation in information retrieval | ppt1 ppt2 pdf pdf | pdf | pdf | src |
| 09 | Relevance feedback & query expansion | ppt1 ppt2 pdf 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 | pdf | src |
| 14 | Vector space classification | ppt1 ppt2 pdf pdf | pdf | pdf | src |
| 15-1 | Support vector machines | ppt1 ppt2 pdf pdf | pdf | pdf | src |
| 15-2 | Learning to rank | ppt1 ppt2 pdf pdf | pdf | pdf | src |
| 16 | Flat clustering | ppt1 ppt2 pdf pdf | pdf | pdf | src |
| 17 | Hierarchical clustering | ppt1 ppt2 pdf pdf | pdf | pdf | src |
| 18 | Matrix decompositions & latent semantic indexing | ppt1 ppt2 pdf pdf | pdf | pdf | src |
| 19 | Web search basics | ppt1 ppt2 pdf pdf | pdf | pdf | src |
| 20 | Web crawling and indexes | ppt1 ppt2 pdf pdf | pdf | pdf | src |
| 21 | Link analysis | ppt1 ppt2 pdf 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.
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