Inhalt

[ 921INSYLUDK13 ] KV Learning from User-generated Data

Versionsauswahl
Workload Education level Study areas Responsible person Hours per week Coordinating university
4,5 ECTS M1 - Master's programme 1. year Computer Science Peter Knees 3 hpw Johannes Kepler University Linz
Detailed information
Original study plan Master's programme Computer Science 2013W
Objectives In this course students will acquire basic knowledge for dealing with used-generated data in the fields of machine learning and pattern recognition. Students will learn about sources and methods for data extraction from Web and social media and techniques for usage of this data. The students' skills will be further developed through a practical project involving work with real-world data.
Subject Knowledge and classification of sources for user-generated data, mining and analysis of Web content and structure, mining and analysis of social media, mining of user behaviour and feedback (explicit and implicit), recommender systems, strategies for personalisation of content and user interfaces, context-aware search, retrieval, and recommendation

Practical project: Using real-world, user-generated data, students will conduct a pattern classification project that requires data extraction, data analysis, feature definition, training of various classifiers, and systematic experimentation.

Criteria for evaluation written exam, practical exercises
Methods lectures, practical exercises
Language English
Study material slides, scientific papers
Changing subject? No
On-site course
Maximum number of participants -
Assignment procedure Direct assignment