Information Retrieval 1 — Overview
Course: Information Retrieval 1 (52041INR6Y) — 2025/26 Sem. 2, Period 4 Programme: MSc Artificial Intelligence, UvA Instructors: Dr. Evangelos Kanoulas, Dr. Maria Heuss, Dr. Maarten de Rijke, Dr. Bhaskar Mitra, Philipp Hager Exam: Written digital exam (ANS), date TBD Week 7+ Cheat sheet: A4, one-side only, handwritten
Textbooks
- SEIRiP: Search Engines: Information Retrieval in Practice — Croft, Metzler, Strohman (online)
- IIR: Introduction to Information Retrieval — Manning, Raghavan, Schütze (online)
- PTR: Pretrained Transformers for Text Ranking: BERT and Beyond — Lin, Nogueira, Yates (online)
- Additional papers referenced in lecture slides
Assessment
| Component | Weight | Notes |
|---|---|---|
| Assignment 0 (Warmup) | PASS/FAIL | Individual, workflow familiarization |
| Assignment 1 (Unsupervised Retrieval) | PASS/FAIL | Pairs, ≥80% automated tests |
| Assignment 2 (Neural Retrieval) | PASS/FAIL | Pairs, due March 5 |
| Assignment 3 | PASS/FAIL | Pairs |
| Paper Presentation | 30% | Pairs, rubric provided |
| Final Exam | 70% | Must score ≥ 5.5 |
Must pass all assignments + ≥5.5 on presentation + ≥5.5 on exam.
Weekly Schedule
Week 1 — Foundations of IR
| Topic | Lecturer | Readings | Notes | |
|---|---|---|---|---|
| L1.1 | Administration & Course Intro | Kanoulas | IR-L01 - Introduction | |
| L1.2 | Introduction to IR | Kanoulas | Lin et al. 1, 2-2.7, 3-3.1 | IR-L02 - IR Fundamentals |
| Reading | SEIRiP 2.3, 4.1-4.3, 5.3, 5.6-5.7, 6.2, 7, 8 | |||
| Assignment | A0: Warmup | IR-A00 - Warmup |
Week 2 — Retrieval Models & Evaluation
| Topic | Lecturer | Readings | Notes | |
|---|---|---|---|---|
| L2 | Term-Based Ranking (BM25, QL, etc.) | Kanoulas | IR-L03 - Retrieval Models | |
| L3 | IR Evaluation | Kanoulas | IR-L04 - Evaluation | |
| Assignment | A1: Unsupervised Retrieval | Due Feb 17 | IR-A01 - Unsupervised Retrieval |
Week 3 — Neural IR
| Topic | Lecturer | Readings | Notes | |
|---|---|---|---|---|
| L4 | Neural IR: Intro & Reranking | Heuss | Lin et al. 2+3 | IR-L05 - Neural IR Intro & Reranking |
| L5 | Dense Retrieval | Heuss | Lin et al. 4+5 | IR-L06 - Dense Retrieval |
| Reading | Dense Text Retrieval Survey |
Week 4 — Advanced Neural IR (current)
| Topic | Lecturer | Readings | Notes | |
|---|---|---|---|---|
| L6 | Learned Sparse Retrieval | Heuss | LSR Tutorial, Unified Framework paper | IR-L07 - Learned Sparse Retrieval |
| L7 | Generative Retrieval (DSI, etc.) | de Rijke | IR-L08 - Generative Retrieval | |
| L8 | RAG | Heuss | IR-L09 - RAG | |
| Assignment | A2: Neural Retrieval | Due March 5 |
Week 5 — Learning to Rank
| Topic | Lecturer | Readings | Notes | |
|---|---|---|---|---|
| L9 | Offline LTR | Hager | LTR for IR 1.2-1.3, 2-2.2.1, 2.4.2, 3, 4.2 | |
| L10 | LTR from Interactions | Hager | Unbiased LTR paper |
Week 6 — Responsible IR
| Topic | Lecturer | Notes | |
|---|---|---|---|
| L11 | Fairness & Biases in IR | Heuss | |
| L12 | Explainable IR / IR & Society | Heuss / Mitra |
Week 7 — Conversational & Wrap-Up
| Topic | Lecturer | Notes | |
|---|---|---|---|
| L13 | Conversational Search & Search R1 | Kanoulas | |
| L14 | Wrap-Up, Q&A, Sample Exam | Kanoulas |
Concept Index
Foundations: Information Retrieval · Inverted Index · Tokenization · Stemming · Stop Words · Bag of Words
Retrieval Models: TF-IDF · BM25 · Query Likelihood Model · Language Model for IR · Vector Space Model
Evaluation: Precision · Recall · F-Measure · MAP · NDCG · MRR · Precision at K
Neural IR: Neural Reranking · Cross-Encoder · Bi-Encoder · Dense Retrieval · Learned Sparse Retrieval · BERT for IR · ColBERT · SPLADE
Generative & RAG: Generative Retrieval · Differentiable Search Index · Retrieval-Augmented Generation
Learning to Rank: Learning to Rank · Pointwise LTR · Pairwise LTR · Listwise LTR · Click Models