| AdMIRe 2012: 4th International Workshop on Advances in Music Information Research: "The Web of Music" in conjunction with the 21st International World Wide Web Conference Location: Lyon, France Date: 17th April 2012 supported by the EU-FP7 project Music Information ReSearch (MIReS)
> AdMIRe 2011, AdMIRe 2010, AdMIRe 2009 |
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| The International
Workshop on Advances in Music Information Research (AdMIRe) serves
as a forum for theoretical and practical discussions of cutting edge
research on Web technologies for music information research. Topics
covered include Web mining for music information extraction, retrieval,
and recommendation as well as mobile applications and services that
make use of Web 2.0 technology. Submissions addressing concrete
implementations of systems and services by both academic institutions
and industrial companies are also welcome. |
| 2012-01-11: Deadlines
extended |
| 2012-01-10: Keynote will be
given by Francesco
Ricci |
| 2011-12-22: Extended versions of
outstanding papers will be published in a Special Issue of the International
Journal of Multimedia Information Retrieval |
| 2011-10-05: Website relaunched |
| Music
information research has been a fast growing field of research during
the past decade. In traditional MIR, music-related information were
extracted from the audio signal using signal processing techniques.
These methods, however, cannot capture semantic information that is not
encoded in the audio signal, but nonetheless essential to many
consumers, e.g., the meaning of the lyrics of a song or the political
motivation or background of a singer. The recent launches of Google Music, Amazon.com’s
Cloud Player and Apple’s iCloud with
iTunes Match
show the huge commercial interest behind music distribution and
consumption. Given the fact that music is an omnipresent topic on the
Web, techniques to mine the Web of Music are vital for music
information research and related applications. In recent years, the emergence of various Web 2.0 platforms and services dedicated or related to the music and audio domain, like last.fm, YouTube, MusicBrainz, Pandora, or echonest, has been providing novel and powerful, albeit noisy, sources for high level, semantic information on music artists, albums, songs, and others. The abundance of such information provided by the power of the crowd can therefore contribute to music information research and development considerably. On the other hand, the wealth of newly available, semantically meaningful information offered on Web 2.0 platforms also poses new challenges, e.g., dealing with the huge amount and the noisiness of this kind of data, various user biases, hacking, or the cold start problem. Another recent trend are innovative user interfaces to access the large amounts of music available on smart mobile devices that are always connected to the Web. Dealing with the vast amounts of music requires new interaction paradigms and intelligent services that provide, for example, personalized and context-aware music recommendations. The current emergence and confluence of these challenges make this an interesting field for researchers and industry practitioners alike. |
 |
Context-Aware Music
Recommender Systems Abstract: Recommender Systems (RSs) are software tools and techniques providing suggestions for items to be of use to a user. The context of an item usage, e.g., when or in which physical environment a music track is played, can influence the user’s emotional response and evaluation for the item. Hence, Music Recommender Systems should take into account this information to deliver more useful (perceived) recommendations. Context modeling and context-dependent reasoning is a complex subject and still there are major technical and practical difficulties to solve: obtain sufficient and reliable data describing the user preferences in context; selecting the right context information, i.e., relevant in a particular personalization task; understanding the impact of the contextual dimensions on the personalization process; embedding the contextual dimensions in a recommendation computational model. These topics will be illustrated in the talk, making examples taken from the music recommender systems that we have developed. Biography: Francesco Ricci is an associate professor of computer science at the Free University of Bozen-Bolzano, Italy. His current research interests include recommender systems, intelligent interfaces, mobile systems, machine learning, case-based reasoning, and the applications of ICT to tourism. He has published more than one hundred of academic papers on these topics. He is on the editorial board of Journal of Information Technology & Tourism and the Journal of User Modeling and User Adapted Interaction. He is member of the steering committee of the ACM Conference on Recommender Systems. He served on the program committees of several conferences, including as a program co-chair of the ACM Conference on Recommender Systems (RecSys), the International Conference on Case-Based Reasoning (ICCBR) and the International Conference on Information and Communication Technologies in Tourism (ENTER). |
| The Call for Papers is available as HTML and as PDF. |
| AdMIRe
2012 solicits regular
technical papers of up to 8
pages following the ACM author guidelines as well as short papers of up to 4 pages. Paper submissions
must be original
and not submitted to or accepted by any other
conference or journal, regardless of the paper type (regular or short).
We will invite authors of particularly
outstanding submissions to publish extended versions in a Special Issue
of the International
Journal of Multimedia Information Retrieval. All submissions to this workshop will be peer-reviewed by at least three Program Committee members. The review process will be double-blind. |
Topics of Interest
| Music Information Systems |
| Multimodal User Interfaces |
| User Modeling, Personalization, Music Recommendation |
| Context-aware and Mobile Music Information Retrieval |
| Music in the Cloud |
| Web Mining and Information Extraction |
| Collaborative Tags, Social Media Mining, (Social) Network Analysis |
| Semantic Content Analysis and Music Indexing |
| Hybrid Approaches using Context and Content |
| Large-Scale Music Similarity Measurement, Scalability Issues and Solutions |
| Evaluation, Mining of Ground Truth and Data Collections |
| Semantic Web, Linked Data, Ontologies, Semantics and Reasoning |
| Mining and Analysis of Music Video Clips, Music-Related Images and Artwork |
| Abstract
Submisson |
2012-01-22 |
| Full Paper Submission | 2012-01-29 |
| Notification of Results | 2012-02-29 |
| Camera Ready Submission | 2012-03-15 |
Organizers and Program Chairs
| Markus Schedl | Department of Computational Perception, Johannes Kepler University, Linz, Austria |
| Peter Knees | Department of Computational Perception, Johannes Kepler University, Linz, Austria |
| Òscar Celma | Gracenote, Emeryville, CA, USA |
Program Committee
| Mathieu Barthet |
Queen Mary University of London, UK |
| Stephan Baumann | German Research Center for AI, Kaiserslautern, Germany |
| Dmitry Bogdanov | Universitat Pompeu Fabra, Barcelona, Spain |
| Ching-Wei Chen | Gracenote, Emeryville, CA, USA |
| Mehdi Elahi |
University of Bolzano-Bozen,
Italy |
| Benjamin Fields | Musicmetric, London, UK |
| Arthur Flexer |
Austrian Research Institute for Artificial Intelligence, Vienna, Austria |
| Emilia Gómez | Universitat Pompeu Fabra, Barcelona, Spain |
| Masataka Goto | National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Japan |
| Fabien Gouyon | Institute for Systems and Computer Engineering of Porto, Portugal |
| Xiao Hu |
University
of Denver, CO, USA |
| Noam Koenigstein | School of Electrical Engineering, Tel Aviv University, Tel Aviv, Israel |
| Ian Knopke |
BBC,
London, UK |
| Paul Lamere | the echonest, Davis Square, Somerville, MA, USA |
| Matthias Mauch |
last.fm,
London, UK |
| Robert Macrae |
SoundHound, San Jose, CA, USA |
| Brian McFee |
University of San Diego, CA, USA |
| Mitsunori Ogihara | University
of Miami, FL, USA |
| Dominik Schnitzer | Austrian Research Institute for Artificial Intelligence, Vienna, Austria |
| Malcolm Slaney | Yahoo! Research Laboratory, Silicon Valley, CA, USA |
| Mohamed Sordo | Universitat Pompeu Fabra, Barcelona, Spain |
| Sebastian Stober | Otto-von-Guericke-Universität Magdeburg, Germany |
| Steve Tjoa | Imagine Research, San Francisco, CA, USA |
| Julián Urbano |
University Carlos III of Madrid, Spain |
| Arjen de Vries |
Centrum Wiskunde & Informatica (CWI), Amsterdam, the Netherlands |
| Jun Wang | Dolby Laboratories, Beijing, P.R. China |
| Geraint Wiggins | Queen Mary University of London, UK |
| Submissions will be managed by EasyChair. Please create a user account if you have not already done so, login and follow the instructions to submit a new paper. |
| Markus
Schedl Department of Computational Perception Johannes Kepler University (JKU) Linz Altenberger Str. 69, A-4040 Linz, Austria Tel:
+43 732 2468 1512 |
