[ 921INSYLUDU21 ] UE Learning from User-generated Data

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