Inhalt
[ 921INSYLUDU21 ] UE Learning from User-generated Data
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| Es ist eine neuere Version 2025W dieser LV im Curriculum Master's programme Business Informatics 2025W vorhanden. |
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| 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 |
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| 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.
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| 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.
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| Criteria for evaluation |
practical exercises
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| Methods |
lectures, practical exercises
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| Language |
English |
| Study material |
slides, scientific papers
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| 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)
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| On-site course |
| Maximum number of participants |
35 |
| Assignment procedure |
Direct assignment |
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