Music context-based information extraction is a hot research topic, not at least because of the enormous rise Social Web usage has encountered during the last couple of years. In this seminar talk, I will present Web-based methods to extract data about music entities (mostly on the level of music artists) and show how such data can be used to build music applications and services. The talk will cover three areas of Web-based MIR:

- music-related information extraction (How to automatically build a music information system?)
- artist similarity measurement using Web pages and using microblogs (tweets)
- popularity estimation (Who's hot?)

For the first topic, I will report on text-based information extraction methods to determine prototypical artists with respect to a certain category (e.g., genre), to perform automated tagging, to retrieve album cover artwork, and to detect band members and instrumentation. As for the similarity measurement task, I will report on large-scale evaluation experiments aimed at determining well-performing parameter settings for modeling the Web-based music similarity space (e.g., TF-, IDF-formulations, normalization strategies, similarity functions). Finally, I will present and compare different techniques to predicting the popularity of a music artist using different data sources (Web, Twitter, last.fm, Peer-to-Peer Networks).

Markus Schedl graduated in Computer Science from the Vienna University of Technology. He earned his Ph.D. in Computational Perception from the Johannes Kepler University Linz, where he is employed as assistant professor at the Department of Computational Perception. He further holds a Master's degree in International Business Administration from the Vienna University of Economics and Business Administration. Schedl (co-)authored more than 40 refereed conference papers and several journal articles. Furthermore, he reviewed submissions to various conferences and articles for the journals IEEE Transactions on Multimedia and Springer Multimedia Systems, as well as for the IEEE Communications Magazine. He is co-founder of the International Workshop on Advances in Music Information Research. His main research interests include Web Mining, Music and Multimedia Information Retrieval, Information Visualization, and Recommendation/Personalization.