Syllabus

Fall 2023

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Week and Date Number of Classes (Lec) Topics Readings Key Activities
Week 1
Aug 28
Aug 30
2 Introduction to IR
Conceptual Models of IR
Boolean Model
Chapter 1, 2
Week 2
Sept 4 (holiday)
Sept 6
1 Tokenization
Text analysis: stop lists, stemming Dictionaries, Tolerant Retrieval
Chapter 3 Supplements Project 1 release
Create accounts - GCP, Social Media (TBD)
Tutorial – SOLR
Week 3
Sept 11, 13
2 Index Construction and Compression Chapter 4 Supplements
Week 4
Sept 18, 20
2 Text Properties (Heaps, Zipfs Laws)
Index Compression, TF-IDF Weighting, Vector-Space Model
Chapter 5, 6 Sept 24 P1 Due
Week 5
Sept 25, 27
2 Scoring and Ranking in IR Systems
Introduction to Embeddings & Latent Semantic Indexing (LSI)
Ch 6, 7, 18 Notes Sept 25 P2 Rel
Week 6
Oct 2, 4
1 Midterm 1
Basics of Deep Learning for IR, Introduction to Transformers & their Role in IR
Notes Midterm 1 - Oct 2
Week 7
Oct 9 (holiday), 11
1 Evaluation in IR 1 Ch 8
Week 8
Oct 16, 18
1 Evaluation in IR 2
Relevance Feedback, Query Expansion
Ch 8,9
Week 9
Oct 23, 25
2 Machine Learned Ranking, Probabilistic IR, Okapi BM25 Ch 11, 12
Week 10
Oct 30, Nov 1
2 Web Search, Web Crawling Ch 19,20 Nov 3 P2 Due
Week 11
Nov 6, 8
2 Social Network Analysis (Link Analysis, PageRank, HITS) Ch 21 Nov 8 P3 Rel
Week 12
Nov 13, 15
1 Midterm 2
Word Vectors in-depth (Word2Vec, GloVe, Doc2Vec)
Notes Midterm 2 - Nov 13
Week 13
Nov 20, 22 (holiday)
1 Intro to Large Language Models & Retrieval Techniques, Intro to Transformers (Self Attention) Notes
Week 14
Nov 27, Nov 29(Cancelled)
1 Hands on Demo
Practical Uses of Word Embeddings
RAG for Question Answering
Notes
Week 15
Dec 4, 6
0 Student Project Presentations P3 due Dec 10

All the chapters are from the book Introduction to Information Retrieval