👷 Introduction to Information Retrieval
Information retrieval by question answering by large language models and Clustering 1. 5. 2024
Lecture
There is no contact lecture this week (state holiday). Self-study materials were commented on and posted in the previous week.
Readings (just for the curious)
Flat clustering
Chapter 16 from the Introduction to Information Retrieval book by Manning et al. (2008)
Hierarchical clustering
Chapter 17 from the Introduction to Information Retrieval book by Manning et al. (2008)
Seminar (holds as usual)
Relevance feedback, Query expansion, Text classification, and Naive Bayes
Exercise assignment for the seminar on relevance feedback
Clustering
Exercise solution for the seminar on clustering
Clustering
Google Colaboratory code for the seminar on clustering
Whiteboard images
Images of the whiteboard (PV211 runs of 2021, 2022)
Second-term project links
Second-term project assignment
CQADupStack Collection and the ARQMath Collection
Below, you can find the homework vaults for submitting the second-term project:
The second project (CQADupStack Collection, 2024)
Homework vault for the second term project (a ranked supervised retrieval system for the CQADupStack Collection).
Alternative second project: (ARQMath Collection, 2024)
Homework vault for the alternative second project (a ranked supervised retrieval system for the ARQMath Collection).
As announced in the course introductory lecture, to verify your approach's originality and help the reviewers assess the quality of your solution, you were asked to accompany your Python notebook with a short Technical Report (max 400 words) for up to 6 points. You may (optionally) use the Technical Report Template. Due to the second term projects of a) ARQMath and b) CQADupStack,