Towards an automatically generated music information system via web content mining

Authors:
Markus Schedl;Peter Knees;Tim Pohle;Gerhard Widmer
Affiliations:
Department of Computational Perception, Johannes Kepler University, Linz, Austria;Department of Computational Perception, Johannes Kepler University, Linz, Austria;Department of Computational Perception, Johannes Kepler University, Linz, Austria;Department of Computational Perception, Johannes Kepler University, Linz, Austria and Austrian Research Institute for Artificial Intelligence, Vienna, Austria
Venue:
ECIR'08 Proceedings of the IR research, 30th European conference on Advances in information retrieval
Year:
2008

Citing 5
Cited 1

Automatic Ontology-Based Knowledge Extraction from Web Documents

IEEE Intelligent Systems
Inverted files for text search engines

ACM Computing Surveys (CSUR)
An innovative three-dimensional user interface for exploring music collections enriched

MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
A music search engine built upon audio-based and web-based similarity measures

SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Towards automatic retrieval of album covers

ECIR'06 Proceedings of the 28th European conference on Advances in Information Retrieval

On the suitability of state-of-the-art music information retrieval methods for analyzing, categorizing and accessing non-Western and ethnic music collections

Signal Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents first steps towards building a music information system like last.fm, but with the major difference that the data is automatically retrieved from the WWW using web content mining techniques. We first review approaches to some major problems of music information retrieval (MIR), which are required to achieve the ultimate aim, and we illustrate how these approaches can be put together to create the automatically generated music information system (AGMIS). The problems addressed in this paper are similar and prototypical artist detection, album cover retrieval, band member and instrumentation detection, automatic tagging of artists, and browsing/exploring web pages related to a music artist. Finally, we elaborate on the currently ongoing work of evaluating the methods on a large dataset of more than 600, 000 music artists and on a first prototypical implementation of AGMIS.