Abstract
Organizing multimedia data is very challenging. One of the most important approaches to support users in searching and navigating media collections is collaborative filtering. Recently, systems as flickr or last.fm have become popular. They allow users to not only rate but also tag items with arbitrary labels. Such systems replace the concept of a global common ontology, as envisioned by the Semantic Web, with a paradigm of heterogeneous, local “folksonomies”. The problem of such tagging systems is, however, that resulting taggings carry only little semantics. In this paper, we present an extension to the tagging approach. We allow tags to be grouped into aspects. We show that introducing aspects does not only help the user to manage large numbers of tags, but also facilitates data mining in various ways. We exemplify our approach on Nemoz, a distributed media organizer based on tagging and distributed data mining.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Shardanand, U., Maes, P.: Social information filtering: Algorithms for automating ”word of mouth”. In: Proceedings of ACM CHI 1995 Conference on Human Factors in Computing Systems, vol. 1, pp. 210–217. ACM Press, New York (1995)
Konstan, J.A., Miller, B.N., Maltz, D., Herlocker, J.L., Gordon, L.R., Riedl, J.: GroupLens: Applying collaborative filtering to Usenet news. Communications of the ACM 40(3), 77–87 (1997)
Linden, G., Smith, B., York, J.: Amazon.com recommendations: item-to-item collaborative filtering. Internet Computing, IEEE 7(1), 76–80 (2003)
Haase, P., Ehrig, M., Hotho, A., Schnizler, B.: Personalized information access in a bibliographic peer-to-peer system. In: Stuckenschmidt, H., Staab, S. (eds.) Semantic Web and Peer-to-Peer, pp. 141–156. Springer, Heidelberg (2005)
Schmitz, C., Hotho, A., Jschke, R., Stumme, G.: Mining association rules in folksonomies. In: Batagelj, V., Bock, H.-H., Ferligoj, A., iberna, A. (eds.) Data Science and Classification. Studies in Classification, Data Analysis, and Knowledge Organization, Berlin, Heidelberg, pp. 261–270. Springer, Heidelberg (2006)
Fielding, R.T.: Architectural styles and the design of network-based software architectures. PhD thesis, University of California (2000)
Baader, F., Calvanese, D., McGuinness, D., Nardi, D., Patel-Schneider, P.: The Description Logic Handbook. Cambridge University Press, Cambridge (UK) (2003)
Guoyon, F., Dixon, S., Pampalk, E., Widmer, G.: Evaluating rhytmic descriptors for musical genre classification. In: Proceedings of the International AES Conference (2004)
Lidy, T., Rauber, A.: Evaluation of feature extractors and psycho-acoustic transformations for music genre classification. In: Proceedings of the International Conference on Music Information Retrieval, pp. 34–41 (2005)
Schedl, M., Pampalk, E., Widmer, G.: Intelligent structuring and exploration of digital music collections. e und i – Elektrotechnik und Informationstechnik 7/8 (2005)
Moerchen, F., Ultsch, A., Thies, M., Loehken, I., Noecker, M., Stamm, C., Efthymiou, N., Kuemmerer, M.: Musicminer: Visualizing perceptual distances of music as topograpical maps. Technical report, Dept. of Mathematics and Computer Science, University of Marburg, Germany (2004)
Stenzel, R., Kamps, T.: Improving content-based similarity measures by training a collaborative model. In: Proceedings of the International Conference on Music Information Retrieval (2005)
Pampalk, E., Widmer, G., Chan, A.: A new approach to hierarchical clustering and structuring of data with self-organizing maps. Intelligent Data Analysis 8(2) (2005)
Logan, B.: Content-based playlist generation: Exploratory experiments. In: Proceedings of the International Symposium on Music Information Retrieval (2002)
Guo, G., Li, S.Z.: Content-Based Audio Classification and Retrieval by Support Vector Machines. IEEE Transaction on Neural Networks 14(1), 209–215 (2003)
Tzanetakis, G.: Manipulation, Analysis and Retrieval Systems for Audio Signals. PhD thesis, Computer Science Department, Princeton University (2002)
Pohle, T., Pampalk, E., Widmer, G.: Evaluation of frequently used audio features for classification of music into perceptual categories. In: CBMI 2005. Proceedings of the Fourth International Workshop on Content-Based Multimedia Indexing (2005)
Mierswa, I., Morik, K.: Automatic feature extraction for classifying audio data. Machine Learning Journal 58, 127–149 (2005)
Zils, A., Pachet, F.: Automatic extraction of music descriptors from acoustic signals using eds. In: Proceedings of the 116th Convention of the AES (2004)
Baumann, S., Hummel, O.: Using cultural metadata for artist recommendations. In: Proceedings of the International Conference on WEB Delivering of Music (2003)
Thrun, S., O’Sullivan, J.: Discovering structure in multiple learning tasks: The TC algorithm. In: Proceedings of the International Conference on Machine Learning (1996)
Mierswa, I., Wurst, M.: Efficient feature construction by meta learning – guiding the search in meta hypothesis space. In: Proceedings of the International Conference on Machine Learning Workshop on Meta Learning (2005)
Cohn, D., Caruana, R., McCallum, A.: Semi-supervised clustering with user feedback. Technical Report TR2003-1892, Cornell University (2000)
Wurst, M., Morik, K., Mierswa, I.: Localized alternative cluster ensembles for collaborative structuring. In: Proceedings of the European Conference on Machine Learning (2006)
Smith, R.B., Maloney, J., Ungar, D.: The self-4.0 user interface: manifesting a system-wide vision of concreteness, uniformity, and flexibility. In: OOPSLA 1995. Proceedings of the tenth annual conference on Object-oriented programming systems, languages, and applications, pp. 47–60. ACM Press, New York (1995)
Moerchen, F., Ultsch, A., Noecker, M., Stamm, C.: Databionic visualization of music collections according to perceptual distance. In: ISMIR, pp. 396–403 (2005)
Knees, P., Schedl, M., Pohle, T., Widmer, G.: An innovative three-dimensional user interface for exploring music collections enriched. In: MULTIMEDIA 2006. Proceedings of the 14th annual ACM international conference on Multimedia, pp. 17–24. ACM Press, New York (2006)
Johnson, B.: Treeviz: treemap visualization of hierarchically structured information. In: CHI 1992. Proceedings of the SIGCHI conference on Human factors in computing systems, pp. 369–370. ACM Press, New York (1992)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Flasch, O., Kaspari, A., Morik, K., Wurst, M. (2007). Aspect-Based Tagging for Collaborative Media Organization. In: Berendt, B., Hotho, A., Mladenic, D., Semeraro, G. (eds) From Web to Social Web: Discovering and Deploying User and Content Profiles. WebMine 2006. Lecture Notes in Computer Science(), vol 4737. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74951-6_7
Download citation
DOI: https://doi.org/10.1007/978-3-540-74951-6_7
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74950-9
Online ISBN: 978-3-540-74951-6
eBook Packages: Computer ScienceComputer Science (R0)