Course Schedule

Aug 26

Introduction to search: Exact-match retrieval

Readings: Ch 5.1

Aug 28

Introduction to search: DAAT, BM25, query operators

Readings: Ch 1, Ch 11.4.3

Sep 1

HW1 out

Sep 2

Introduction to search: QryEval

Readings:Ch 2.4.2

Sep 4

Offline evaluation

Readings: Ch 8-8.5

Sep 9

Best-match retrieval: VSM, language models

Readings: Ch 6.2-6.4.2, Ch 12.2-12.4

Sep 11

Online evaluation

Readings: Kelly and Teevan, 2003, Jiang et al., 2014

Sep 15

HW1 due, HW2 out

Sep 16

Feature-based ranking models

Readings: Li, 2011

Sep 18

Feature-based ranking models, Authority metrics

Readings: Ch 21 - 21.2

Sep 23,

Recommender systems: Introduction and basic algorithms

Readings: Personalized Machine Learning (Ch 4), Fairness in Information Access Systems (Ch 2)

Sep 25

Recommender systems: Feature-based models

Readings: Personalized Machine Learning (Ch 5), Covington, et al., 2016

Sep 29

HW2 due, HW3 out

Sep 30

Index creation

Readings: Ch 4-4.5, Ch 5.3-5.3.1, Ch 2.3, Ch 7.1.3

Oct 2

Large-scale indexes

Readings:

Oct 7

Personalization

Readings: Eickhoff et al, 2014, Bennett et al, 2012

Oct 9

Midterm exam

Readings: Sample Midterm, additional questions

Oct 20

HW3 due, HW4 out

Oct 21

Neural ranking models: Introduction

Readings:

Oct 25

Neural ranking models: BERT reranking

Readings: Dai & Callan, 2019a

Oct 28

Neural ranking models: Sparse models

Readings: Dai & Callan, 2019b

Oct 30

Neural ranking models: Dense models

Readings: Karpukhin, et al., 2020

Nov 3

HW4 due, HW5 out

Nov 6

Neural ranking models: Large language models

Readings:

Nov 11

Neural ranking models: Retrieval augmented generation

Readings: Gao, et al., 2023

Nov 13

Diversification: measurement

Readings:

Nov 17

HW5 due

Nov 18

Diversification: optimization

Readings: Dang & Croft, 2012, Santos, et al., 2010

Nov 20

Fairness: measurement

Readings:

Nov 25

Fairness: optimization

Readings:  

Dec 2

Evaluating with search logs

Readings:

Dec 4

Final exam

Readings: Sample Final