Digicampus
Lecture: Search Engines and Neural Information Retrieval (Lecture) - Details
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Lehrveranstaltung wird in Präsenz abgehalten.

General information

Course name Lecture: Search Engines and Neural Information Retrieval (Lecture)
Course number INF-0506
Semester SS 2024
Current number of participants 16
Home institute Professur für Sprachverstehen mit Anwendung Digital Humanities
Courses type Lecture in category Teaching
Next date Friday, 31.05.2024 08:20 - 09:50, Room: (202 F1 (Alte Uni))
Type/Form Interactive teaching (on-site) with self-study components
Online/Digitale Veranstaltung Veranstaltung wird in Präsenz abgehalten.
Hauptunterrichtssprache englisch
ECTS points 8

Rooms and times

(202 F1 (Alte Uni))
Friday: 08:20 - 09:50, weekly (13x)
Friday: 10:00 - 11:30, weekly (13x)
Friday: 12:15 - 13:45, weekly (13x)
(F2 503 (Alte Uni))
Friday: 08:20 - 09:50, weekly (1x)
Friday: 10:00 - 11:30, weekly (1x)
Friday: 12:15 - 13:45, weekly (1x)

Module assignments

Comment/Description

Neural Information Retrieval leverages the power of neural networks to enhance the representation, understanding, and retrieval of information, addressing many of the challenges posed by the complexity and variability of natural language. With the recent development in the area of large language models (or more generally, foundation models), novel approaches to interactive information retrieval are developing.

After taking part in the event, students are able to explain the concepts and methods, procedures, techniques and technologies related to neural information retrieval. In particular, the course covers:
• Basics of traditional information retrieval methods
• Vector-based document and query representations (topic modeling and neural representations)
• Ranking with embeddings
• Question answering, entity search, and knowledge graphs
• Multimodal retrieval
• Interactive information retrieval and personalization

This on-site course will be taught in an interactive way.
NOTE: The exercise session currently overlaps with the lecture Probabilistic Machine Learning lecture. In case you are planning to take both courses, please contact me. Another potential time slot for the tutorial session would be Wednesdays 8.15am (on campus). In this interactive course, there is no strict separation between lecture and tutorial, hence, it is important to participate in all sessions.