People associate Music sometimes with very different Moods and Emotions and prefer hence in different situations another background music. What is for someone the perfect music choice for relaxion after a stressful working day can for someone else in the extreme case evoke stress. Often someone associates with a single music calmness, sometimes one associates with a special artist or a whole style of music a specific personal experiences or special moments. For instance, a certain piece of music might remind you of a special experience of your youth und the connected associations, while another piece could remind you of a holiday passed in a certain country or town allthough the music have no direct reference to it. Such personal associations are an important aspect of handling music. In existing systems which should ease the access to digital music these personal aspects are insufficiently taken into account. Information about the user are often only rudimentary gathered and modeled. A main goal of our research is to contribute to a better integration and modelling of user specific information.

• AUCOMA MusicGalaxy (Video)
• AUCOMA Beatles Explorer (Flash Video)
• AUCOMA Beatles Explorer Presentation (Video)

• Sebastian Stober & Andreas Nürnberger. Visualisierung von großen Musiksammlungen unter Berücksichtigung projektionsbedingter Verzerrungen. In: 36. Jahrestagung für Akustik DAGA 2010, Berlin, German Acoustical Society (DEGA), Berlin, Mar 2010.
• Sebastian Stober; Matthias Steinbrecher & Andreas Nürnberger. A Survey on the Acceptance of Listening Context Logging for MIR Applications. In Stephan Baumann; Juan José Burred; Andreas Nürnberger & Sebastian Stober (eds.): Proceedings of the 3rd Workshop on Learning the Semantics of Audio Signals (LSAS), Pages 45-57, Graz, Austria, Dec 2009.
• Korinna Bade; Jörg Garbers; Sebastian Stober; Frans Wiering & Andreas Nürnberger. Supporting Folk-Song Research by Automatic Metric Learning and Ranking. In: Proceedings of the 10th International Conference on Music Information Retrieval, ISMIR, Pages 741-746, Kobe, Japan, Oct 2009.
• Korinna Bade; Andreas Nürnberger & Sebastian Stober. Everything in its right place? Learning a user's view of a music collection. In: Proceedings of NAG/DAGA 2009, International Conference on Acoustics, Rotterdam, Pages 344-347, German Acoustical Society (DEGA), Berlin, 2009.
• Sebastian Stober & Andreas Nürnberger. User-Adaptive Music Information Retrieval. In: KI Volume 23, Number 2, Pages 54-57, 2009.
• Sebastian Stober and Andreas Nürnberger. Towards User-Adaptive Structuring and Organization of Music Collections. In: Proc. of the 6th Intl. Workshop on Adaptive Multimedial Retrieval (AMR 2008), 2008.
• Valentin Laube, Christian Moewes and Sebastian Stober. Browsing Music by Usage Context. In: Proc. of the 2nd Workshop on Learning the Semantics of Audio Signals (LSAS 2008), pp. 19-29, 2008.
• Johannes Reinhard, Sebastian Stober and Andreas Nürnberger. Enhancing Chord Classification through Neighbourhood Histograms. In: Proc. of the 6th Intl. Workshop on Content-Based Multimedia Indexing (CBMI 2008), 2008.
• Sebastian Stober and Andreas Nürnberger. AUCOMA - Adaptive Nutzerzentrierte Organisation von Musikarchiven. In Ute Jekosch & Rüdiger Hoffmann (eds.): Fortschritte der Akustik: Plenarvorträge und Fachbeiträge der 34. Deutschen Jahrestagung für Akustik DAGA 2008, Dresden, pp. 547-548, DEGA, Berlin, Mar 2008. (in German)
• Alexander Duda, Sebastian Stober and Andreas Nürnberger,  Towards Query by Singing/Humming on Audio Databases, in: Proc. of 8th Intl. Conf. on Music Information Retrieval (ISMIR 2007), pp. 331-334, 2007.
• Knut Hartmann, Daniel Büchner, Alexander Berndt, Carsten Lange und Andreas Nürnberger, Interactive data mining & machine learning techniques for musicology, in: K. Maimets-Volk, R. Parncutt, M. Marin und J. Ross (Hrsg.),  Proc. of the 3rd Conf. on Interdisciplinary Musicology (CIM07), 2007.