Course in Information Retrieval
General Information
Lecturer | Jun.-Prof. Dr. Martin Potthast |
Lab Advisors | Kim Bürgl, Theresa Elstner |
Workload | 2 SWS Lecture, 1 SWS Lab |
Lecture | Monday, 11:15 - 12:45, starting April 11th 2022, Felix-Klein-Hs, Paulinum |
Lab | Tuesday, 9:15 - 10:45, starting April 12th 2022, Felix-Klein-Hs, Paulinum |
Contact | |
Exam | 22.07.2022 12:30 pm. Lecture hall 3 |
Exam
- Exam will take place: 22.07.2022 12:30 pm at Lecture hall 3 (Hörsaalgebäude - Hörsaal 3). Please arrive at least 15 minutes early (room will be open from 12:00)
- You are allowed to bring a handwritten sheet (DIN A4, one side only) with useful information into the exam. The sheet is collected together with the exam at the end of the exam.
- Also allowed to use during the exam is a non-programmable calculator.
Announcements
- Please sign this informed consent that allows us to use your data in the SharKI research project. You can hand us the signed documents either in the next exercise session, or drop it in our mailbox "Sekretariat Petra Gamrath" in Augusteum, 5th floow, room A 514. As mentioned in the last lab session, this is voluntary and does not affect your participation in the class but your signature helps us to do our research. Thank you!
Organization
- Lectures are prerecorded. The videos can be accessed by following the lecturenotes below, or on the Webis youtube channel. [playlist]
- Lab and corresponding material consists of biweekly programming exercises in the form of Jupyter notebooks.
- Examination will take place as written exam.
- Communication
- Lecture website - materials and announcements will be uploaded on this website.
- Email - important announcements will be sent out via mail.
- Moodle - lab project organization.
Lecturenotes
- Information Retrieval » Introduction » Organization, Literature [video 1]
- Information Retrieval » Introduction » Retrieval Problems [video 2] [video 3] [video 4] [video 5] [video 6]
-
Information Retrieval »
Introduction »
Architecture of a Search Engine
[video 7]
[video 8]
[video 9]
[video 10]
[video 11]
[video 12]
[video 13]
[video 14]
- Natural Language Processing » Words » Text Preprocessing [video 15]
-
Natural Language Processing »
Words »
Morphological Analysis
[video 16]
- Information Retrieval » Indexing » Indexing Basics [video 17]
-
Information Retrieval »
Indexing »
Inverted Index
[video 18]
[video 19]
[video 20]
[video 21]
- Information Retrieval » Retrieval Models » Overview of Retrieval Models [video 22]
- Information Retrieval » Retrieval Models » Empirical Models [video 23]
- Machine Learning » Statistical Learning » Probability Basics [video 24] [video 25]
- Machine Learning » Statistical Learning » Bayes Classification [video 26]
- Information Retrieval » Retrieval Models » Probabilistic Models [video 27] [video 28]
-
Information Retrieval »
Retrieval Models »
Generative Models
[video 29]
- Information Retrieval » Evaluation » Laboratory Experiments [video 30]
- Information Retrieval » Evaluation » Effectiveness Measures [video 31] [video 32] [video 33]
-
Information Retrieval »
Evaluation »
Training and Testing
[video 34]
Lab
The lab exercises will give a hands-on experience for the concepts taught in the lecture. Each lecture block will be accompanied by a Jupyter notebook, which implements a component of a basic search engine.
Exercises will be published here every two weeks, with the solution following one week later.
The lab project consists of building and evaluating an information system for a specific domain. This entails related work search, data cleansing, indexing, selection and implementation of suitable retrieval models, evaluation of search quality, and the submission of a written report and well-documented source code.
Lab project material will be published here over the course of the semester.
Lab Lecturenotes
- Introduction
- Lecturenotes Generic » Scientific Toolbox » Literature Research [video 1]
- Lecturenotes Generic » Scientific Toolbox » Scientific Writing [video 3]
Lab Sessions
- 2021/04/12 - Session 01: Introduction, Literature Research, Exercises 01 and 02
- 2021/04/26 - Session 02: Exercise 03
- 2021/05/10 - Session 03: Scientific writing, lab project organisation and Q&A
- 2021/05/24 - Session 04: Exercise 04
- 2021/06/07 - Session 05: Exercise 05
- 2021/06/21 - Session 06: Exercise 06 - takes place in Seminargebäude, room 420
- 2021/07/05 - Session 07: Exercise 07
Lab Exercises
- 00 - Getting Started [download]
- 01 - Introduction to Python [view] [download]
- 02 - Introduction to Jupyter [view] [download]
- 03 - Text Analysis [view notebook] [download notebook] [download data] [view solution] [download solution]
- 04 - Indexing [view notebook] [download notebook] [download preprocess.py] [view solution] [download solution]
- 05 - Basic Retrieval [view notebook] [download notebook] [download preprocess.py] [download indexing.py] [download shakespeare.py] [view solution] [download solution]
- 06 - Advanced Retrieval [view notebook] [download notebook] [download preprocess.py] [download indexing.py] [download shakespeare.py] [view solution] [download solution]
- 06 - Evaluation [view notebook] [download notebook] [download preprocess.py] [download indexing_np.py] [download models.py] [download system.py] [download data]