CSCE 670 - Information Storage and Retrieval (Fall 2025)

Course Information

Instructor: Yu Zhang (yuzhang [AT] tamu [DOT] edu)
TA: Hangxiao Zhu (hangxiao [AT] tamu [DOT] edu)
Lectures:
- Time: Tuesdays and Thursdays 5:30pm – 6:45pm
- Location: HRBB 113
Instructor Office Hour:
- Time: Thursdays 4pm – 5pm
- Location: PETR 222
TA Office Hour:
- Time: Tuesdays 3pm – 4pm
- Location: PETR 448
Syllabus: PDF
Zoom Link (for Guest Lectures): https://tamu.zoom.us/j/6411788612

Grading

Homework: 30%
- Homework 0: 2% [due Sep 6]
- Homework 1: 7% [due Sep 20]
- Homework 2: 7% [due Oct 11]
- Homework 3: 7% [due Nov 1]
- Homework 4: 7% [due Nov 22]
Quizzes: 20%
- Quiz 1: 5% [in the Sep 18 class]
- Quiz 2: 5% [in the Oct 7 class]
- Quiz 3: 5% [in the Oct 30 class]
- Quiz 4: 5% [in the Nov 20 class]
Group Project: 20%
- Presentation: 10% [in the Dec 2 and Dec 4 classes]
- Report: 10% [due Dec 9]
Final: 30% [3:30pm – 5:30pm, Dec 16, HRBB 113]

Schedule (Subject to changes)

Week	Date	Topic	Readings
W1	8/26	Overview and Course Logistics	-
	8/28	Boolean Retrieval	[MRS Chapter 1], [MRS Chapter 2]
W2	9/2	Vector Space Model, TF-IDF	[MRS Chapter 6]
	9/4	Probabilistic Model, BM25	[MRS Chapter 11]
	9/6	Homework 0 Due (Saturday)
W3	9/9	Link Analysis: PageRank	[MRS Chapter 21], [LRU Chapter 5.1/5.2]
	9/11	Link Analysis: Topic-Sensitive PageRank, HITS	[LRU Chapter 5.3/5.5]
W4	9/16	Evaluation	[MRS Chapter 8]
	9/18	Evaluation (Cont'd) and Quiz 1	[MRS Chapter 8]
	9/20	Homework 1 Due (Saturday)
W5	9/23	Learning to Rank	[MRS Chapter 13], [MRS Chapter 14], [Nallapati, SIGIR'04]
	9/25	Learning to Rank (Cont'd)	[Joachims, KDD'02], [Burges et al., ICML'05]
W6	9/30	Recommender Systems: Collaborative Filtering	[LRU Chapter 9.1/9.3]
	9/25	Recommender Systems: Content-Based Approach, Matrix Factorization	[LRU Chapter 9.2/9.4]
W7	10/7	Recommender Systems: Matrix Factorization (Cont'd) and Quiz 2	[LRU Chapter 9.4]
	10/9	Recommender Systems: Bayesian Personalized Ranking	[Rendle et al., UAI'09]
	10/11	Homework 2 Due (Saturday)
W8	10/14	No Class (Fall Break)
	10/16	Word Embedding, word2vec, GloVe	[Mikolov et al., NIPS'13], [Pennington et al., EMNLP'14]
W9	10/21	Neural Ranking	[Nalisnick et al., WWW'16], [Mitra et al., WWW'17]
	10/23	Contextualized Language Models, BERT	[Vaswani et al., NIPS'17], [Devlin et al., NAACL'19]
W10	10/28	Dense Passage Retrieval, ColBERT	[Karpukhin et al., EMNLP'20], [Khattab and Zaharia, SIGIR'20]
	10/30	Neural Collaborative Filtering and Quiz 3	[He et al., WWW'17], [Dacrema et al., RecSys'19]
	11/1	Homework 3 Due (Saturday)
W11	11/4	Sequential Recommendation	[He and McAuley, ICDM'16], [He et al., RecSys'17]
	11/6	Large Language Models Basics	[Brown et al., NeurIPS'20], [Wei et al., ICLR'22], [Ouyang et al., NeurIPS'22], [Wei et al., NeurIPS'22], [Wang et al., ICLR'23], [Schick et al., NeurIPS'23]
W12	11/11	Large Language Models with Search Engines (Guest Lecture by Bowen Jin)	[Jin et al., arXiv'25]
	11/13	Large Language Models for Ranking	[Sun et al., EMNLP'23], [Qin et al., NAACL'24]
W13	11/18	Large Language Models for Ranking (Cont'd) and Recommendation	[Ma et al., SIGIR'24], [Liu et al., arXiv'23]
	11/20	Large Language Models for Recommendation (Cont'd) and Quiz 4	[Hou et al., ECIR'24]
	11/22	Homework 4 Due (Saturday)
W14	11/25	Information Retrieval for Science and Scientific Research	[Zhang et al., EMNLP'23], [Zhang et al., WWW'25]
	11/27	No Class (Thanksgiving)
W15	12/2	Project Presentations
	12/4	Project Presentations