magistraleinformatica:ir:ir22:start
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Entrambe le parti precedenti la revisioneRevisione precedenteProssima revisione | Revisione precedente | ||
magistraleinformatica:ir:ir22:start [13/12/2022 alle 16:35 (3 anni fa)] – [Exams] Paolo Ferragina | magistraleinformatica:ir:ir22:start [07/09/2023 alle 14:00 (22 mesi fa)] (versione attuale) – [Exams] Paolo Ferragina | ||
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====== Exams ====== | ====== Exams ====== | ||
- | The exam will consist of a written test including two parts: **exercises and " | + | The exam will consist of a written test including two parts: **exercises and " |
The first (exercises) and the second (theory questions) parts of the exam can be split into different exam dates, even of different exam sessions. The exam dates are the ones indicated in the calendar on ESAMI. In the case that the second part is not passed or the student abandons the exam, (s)he can keep the rank of the first exam, but this may occur just once. The second time this happens, the rank of the first part is dropped, and the student has to do both parts again. | The first (exercises) and the second (theory questions) parts of the exam can be split into different exam dates, even of different exam sessions. The exam dates are the ones indicated in the calendar on ESAMI. In the case that the second part is not passed or the student abandons the exam, (s)he can keep the rank of the first exam, but this may occur just once. The second time this happens, the rank of the first part is dropped, and the student has to do both parts again. | ||
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^ Date ^ Room ^ Text ^ Notes | | ^ Date ^ Room ^ Text ^ Notes | | ||
- | | 17/01/23, start at 09:00 | room E | text, results, | + | | 17/01/23, start at 09:00 | room E | {{ : |
- | | 08/02/23, start at 09:00 | room E | text, results, solution | | | + | | 08/02/23, start at 11:00 | room A1 | {{ : |
+ | | 05/06/2023, start at 16:00 | room C | {{ : | ||
+ | | 05/07/2023, start at 11:00 | room A1 | {{ : | ||
+ | | 24/07/2023, start at 14:00 | room C | {{ : | ||
+ | | 07/09/2023, start at 14:00 | room A1 | {{ : | ||
====== Materials for study ====== | ====== Materials for study ====== | ||
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* **[MRS]** C.D. Manning, P. Raghavan, H. Schutze. // | * **[MRS]** C.D. Manning, P. Raghavan, H. Schutze. // | ||
* Some copies of papers or notes (linked below). | * Some copies of papers or notes (linked below). | ||
+ | * If you need to practice with exercises given at previous exams, please look at the [[http:// | ||
\\ | \\ | ||
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| 07.11.2022 | Query processing: soft-AND. Phrase queries, biword index and positional index. Exact search: hashing. Prefix search: compacted trie, front coding, 2-level indexing. Edit distance with e-errors via brute-force approach, or Dynamic Programming (possibly weighted). Overlap measure with k-gram index. An index for e-error matches based on k-gram index (with false positives, no false negatives). | Sect. 2.3 and 2.4 of [MRS].\\ [[https:// | | 07.11.2022 | Query processing: soft-AND. Phrase queries, biword index and positional index. Exact search: hashing. Prefix search: compacted trie, front coding, 2-level indexing. Edit distance with e-errors via brute-force approach, or Dynamic Programming (possibly weighted). Overlap measure with k-gram index. An index for e-error matches based on k-gram index (with false positives, no false negatives). | Sect. 2.3 and 2.4 of [MRS].\\ [[https:// | ||
| 08.11.2022 | Caching and Tiered index. An efficient filter for one-error match (with false positives, no false negatives). | | 08.11.2022 | Caching and Tiered index. An efficient filter for one-error match (with false positives, no false negatives). | ||
- | | 14.11.2022 | Text-based ranking: dice, jaccard, tf-idf. Vector space model and cosine similarity doc-doc and query-doc. Storage of tf-idf and use for computing document-query similarity. Fast top-k retrieval: high idf, champion lists, many query terms, clustering.| Sect 6.2 and 6.3 and 7 from [MRS], [[https:// | + | | 14.11.2022 | Text-based ranking: dice, jaccard, tf-idf. Vector space model and cosine similarity doc-doc and query-doc. Storage of tf-idf and use for computing document-query similarity. Fast top-k retrieval: high idf, champion lists, many query terms, clustering.| Sect 6.2 and 6.3 and 7 from [MRS], [[https:// |
| 15.11.2022 | Fast top-k retrieval: fancy hits. Exact Top-K: WAND and blocked-WAND. | | | | 15.11.2022 | Fast top-k retrieval: fancy hits. Exact Top-K: WAND and blocked-WAND. | | | ||
| 21.11.2022 | Relevance feedback, Rocchio, pseudo-relevance feedback, query expansion. Performance measures: precision, recall, F1, DCG and NDCG. | Sect 8.1-8.3 and 9 [MRS]. | | | 21.11.2022 | Relevance feedback, Rocchio, pseudo-relevance feedback, query expansion. Performance measures: precision, recall, F1, DCG and NDCG. | Sect 8.1-8.3 and 9 [MRS]. | |
magistraleinformatica/ir/ir22/start.1670949314.txt.gz · Ultima modifica: 13/12/2022 alle 16:35 (3 anni fa) da Paolo Ferragina