Studienhandbuch | UE Learning from User-generated Data

Inhalt

Workload	Education level	Study areas	Responsible person	Hours per week	Coordinating university
1,5 ECTS	M1 - Master's programme 1. year	Computer Science	Markus Schedl	1 hpw	Johannes Kepler University Linz

Detailed information
Original study plan	Master's programme Computer Science 2021S
Objectives	This course complements the Learning from User-generated Data VL with a series of practical exercises. Through them participants will learn to systematically approach tasks involving large volumes of user-generated data as well as apply commonly used techniques to real-world datasets. The exercises focus on understanding the rationale behind each approach, along with its strengths and weaknesses.
Subject	Mining of user behaviour and feedback data (explicit and implicit), recommender systems, strategies for personalisation of content and user interfaces, context-aware search, retrieval, and recommendation. In the series of exercises ranging from writing standalone functions to building experimental setups, participants will use real-world, user-generated data to solve such tasks as data extraction and preparation, data analysis, classification, feature definition, training of various classifiers, recommendation algorithms, and other.
Criteria for evaluation	practical exercises
Methods	lectures, practical exercises
Language	English
Study material	slides, scientific papers
Changing subject?	No
Corresponding lecture	in collaboration with 921INSYLUDV21: VL Learning from User-generated Data (3 ECTS) equivalent to 921INSYLUDK13: KV Learning from User-generated Data (4.5 ECTS)

On-site course
Maximum number of participants	35
Assignment procedure	Direct assignment