# Learning to Rank

*Student seminar — Session 22*

## Focus

Learning to rank: problem settings (pointwise, pairwise, listwise), evaluation metrics (Precision@k, MAP, NDCG), and representative methods.

## Reading (examples)

- Zaki & Meira, ranking / evaluation chapters
- Liu, *Learning to Rank for Information Retrieval* (selected sections)
- A recent survey or application paper (to be assigned)

## Student tasks

- Explain the problem formalization and assumptions
- Present one method and its objective/loss
- Discuss evaluation protocol and limitations
- Q&A and short discussion