Abstract
In this chapter we present the network-centric evaluation approach. This method analyses the similarity network, created using any recommendation algorithm. Network-centric evaluation uses complex networks analysis to characterise the item collection. Also, we can combine the results from the network analysis with the popularity of the items, using the Long Tail model.
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
P. Cano, M. Koppenberger, and N. Wack, “An industrial-strength content-based music recommendation system,” in Proceedings of 28th International ACM SIGIR Conference, (Salvador, Brazil), 2005.
D. J. Watts and S. H. Strogatz, “Collective dynamics of ‘small-world’ networks,” Nature, vol. 393, pp. 440–442, June 1998.
J. M. Kleinberg, “Navigation in a small world,” Nature, vol. 406, p. 845, 2000.
M. E. J. Newman, “The structure and function of complex networks,” SIAM Review, vol. 45, no. 2, pp. 167–256, 2003.
A. Clauset, C. R. Shalizi and M. E. J. Newman, “Power-law distributions in empirical data,” SIAM Reviews, June 2007.
A.-L. Barabási, R. Albert, H. Jeong, and G. Bianconi, “Power-law distribution of the world wide web,” Science, vol. 287, p. 2115a, 2000.
A. L. Barabási and R. Albert, “Emergence of scaling in random networks,” Science, vol. 286, pp. 509–512, October 1999.
M. Sordo, O. Celma, M. Blech, and E. Guaus, “The quest for musical genres: Do the experts and the wisdom of crowds agree?” in Proceedings of the 9th International Conference on Music Information Retrieval, (Philadelphia, PA), 2008.
K. Jacobson and M. Sandler, “Musically meaningful or just noise? an analysis of on-line artist networks,” in Proceedings of the 6th International Symposium on Computer Music Modeling and Retrieval, (Copenhagen, Denmark), 2008.
P. Meyn and R. L. Tweedie, Markov Chains and Stochastic Stability. London: Springer, 1993.
J. Salganik, P. S. Dodds, and D. J. Watts, “Experimental study of inequality and unpredictability in an artificial cultural market,” Science, vol. 311, pp. 854–856, February 2006.
E. Ravasz and A. L. Barabási, “Hierarchical organization in complex networks,” Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics, vol. 67, February 2003.
S. M. McNee, J. Riedl, and J. A. Konstan, “Being accurate is not enough: how accuracy metrics have hurt recommender systems,” in Computer Human Interaction. Human Factors in Computing Systems, (New York, NY), pp. 1097–1101, ACM, 2006.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2010 Springer Berlin Heidelberg
About this chapter
Cite this chapter
Celma, Ò. (2010). Network-Centric Evaluation. In: Music Recommendation and Discovery. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13287-2_6
Download citation
DOI: https://doi.org/10.1007/978-3-642-13287-2_6
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-13286-5
Online ISBN: 978-3-642-13287-2
eBook Packages: Computer ScienceComputer Science (R0)