A music information system automatically generated via Web content mining techniques

Information Processing and Management

Volumn 47, Issue 3, 2011, Pages 426-439

  Schedl, Markus ^a   Widmer, Gerhard ^a   Knees, Peter ^a   Pohle, Tim ^a  

^a JOHANNES KEPLER UNIVERSITY LINZ   (Austria)

Author keywords

Application; Evaluation; Information systems; Music information retrieval; Web content mining

Indexed keywords

AUTOMATICALLY GENERATED; EVALUATION; EVALUATION EXPERIMENTS; MUSIC INFORMATION RETRIEVAL; NOVEL TECHNIQUES; WEB CONTENT MINING; WEB PAGE;

COMPUTER MUSIC; ELECTRONIC MUSICAL INSTRUMENTS; INFORMATION RETRIEVAL; INFORMATION SYSTEMS; NATURAL LANGUAGE PROCESSING SYSTEMS; WEBSITES;

SEARCH ENGINES;

EID: 79953251129     PISSN: 03064573     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ipm.2010.09.002     Document Type: Article

References (62)

1. H. Alani, S. Kim, D.E. Millard, M.J. Weal, W. Hall, and P.H. Lewis Automatic ontology-based knowledge extraction from web documents IEEE Intelligent Systems 18 1 2003 14 21
2. amgabout (2007). < http://www.allmusic.com/cg/amg.dll?p=amg&sql= 32:amg/info-pages/a-about.html > Accessed November 2007.
3. amg (2009). < http://www.allmusic.com > Accessed November 2009.
4. Andrews, K.; & Heidegger, H. (1998). Information slices: Visualising and exploring large hierarchies using cascading, semi-circular discs. In Proceedings of IEEE information visualization 1998. Research Triangle Park, NC, USA.
5. Aucouturier, J.-J.; & Pachet, F. (2002). Scaling up music playlist generation. In Proceedings of the IEEE international conference on multimedia and expo (ICME 2002) (pp. 105-108). Lausanne, Switzerland.
6. J.-J. Aucouturier, and F. Pachet Improving timbre similarity: How high is the sky? Journal of Negative Results in Speech and Audio Sciences 1 1 2004
7. J.-J. Aucouturier, F. Pachet, and M. Sandler The way it sounds: Timbre models for analysis and retrieval of music signals IEEE Transactions on Multimedia 7 6 2005 1028 1035 (Pubitemid 41789115)
8. Bayer, R. (1971). Binary B-trees for virtual memory. In Proceedings of the ACM SIG FIDET workshop. San Diego, CA, USA.
9. Cano, P.; & Koppenberger, M. (2004). The emergence of complex network patterns in music artist networks. In Proceedings of the 5th international symposium on music information retrieval (ISMIR 2004) (pp. 466-469). Barcelona, Spain.
10. Celma, O. (2008). Music recommendation and discovery in the long tail. Ph.D. Thesis, Universitat Pompeu Fabra, Barcelona, Spain. < http://mtg.upf.edu/ocelma/PhD/doc/ocelma-thesis.pdf >.
11. Celma, O.; & Lamere, P. (2007). ISMIR 2007 tutorial: Music recommendation. < http://mtg.upf.edu/∼ocelma/MusicRecommendationTutorial- ISMIR2007 > Accessed December 2007.
12. S. Chakrabarti, M. van den Berg, and B. Dom Focused crawling: A new approach to topic-specific web resource discovery Computer Networks 31 11-16 1999 1623 1640
13. Cohen, W. W.; Ravikumar, P.; & Fienberg, S. E. (2003). A comparison of string distance metrics for name-matching tasks. In Proceedings of the IJCAI-03 workshop on information integration on the web (IIWeb-03) (pp. 73-78). Acapulco, Mexico.
14. W.W. Cohen, and W. Fan Web-collaborative filtering: Recommending music by crawling the web WWW9/Computer Networks 33 1-6 2000 685 698
15. dis (2009). < http://www.discogs.com > Accessed October 2009.
16. Dixon, S.; Gouyon, F.; & Widmer, G. (2004). Towards characterisation of music via rhythmic patterns. In Proceedings of the 5th international symposium on music information retrieval (ISMIR 2004) (pp. 509-516). Barcelona, Spain.
17. J.S. Downie Music information retrieval Annual Review of Information Science and Technology 37 2003 295 340 (Pubitemid 36116224)
18. Eck, D.; Bertin-Mahieux, T.; & Lamere, P. (2007). Autotagging music using supervised machine learning. In Proceedings of the 8th international conference on music information retrieval (ISMIR 2007). Vienna, Austria.
19. Ellis, D. P.; Whitman, B.; Berenzweig, A.; & Lawrence, S. (2002). The quest for ground truth in musical artist similarity. In Proceedings of 3rd international conference on music information retrieval (ISMIR 2002). Paris, France.
20. exa (2009). < http://www.exalead.com > Accessed February 2009.
21. M. Friedman A comparison of alternative tests of significance for the problem of m rankings The Annals of Mathematical Statistics 11 1 1940 86 92
22. Geleijnse, G.; & Korst, J. (2006). Web-based artist categorization. In Proceedings of the 7th international conference on music information retrieval (ISMIR 2006). Victoria, Canada.
23. Geleijnse, G.; Schedl, M.; & Knees, P. (2007). The quest for ground truth in musical artist tagging in the social web era. In Proceedings of the 8th international conference on music information retrieval (ISMIR 2007). Vienna, Austria.
24. goo (2009). < http://www.google.com > Accessed March 2009.
25. Hu, X.; Bay, M.; & Downie, J. S. (2007). Creating a simplified music mood classification ground-truth set. In Proceedings of the 8th international conference on music information retrieval (ISMIR 2007). Vienna, Austria.
26. isp (2006). < http://wordlist.sourceforge.net > Accessed June 2006.
27. Knees, P.; Pampalk, E.; & Widmer, G. (2004). Artist classification with web-based data. In Proceedings of the 5th international symposium on music information retrieval (ISMIR 2004) (pp. 517-524). Barcelona, Spain.
28. Knees, P.; Schedl, M.; & Widmer, G. (2005). Multiple lyrics alignment: automatic retrieval of song lyrics. In Proceedings of 6th international conference on music information retrieval (ISMIR 2005) (pp. 564-569). London, UK.
29. Knees, P.; Schedl, M.; Pohle, T.; & Widmer, G. (2006). An innovative three-dimensional user interface for exploring music collections enriched with meta-information from the web. In Proceedings of the 14th ACM international conference on multimedia (MM 2006). Santa Barbara, CA, USA.
30. Knees, P.; Pohle, T.; Schedl, M.; & Widmer, G. (2007). A music search engine built upon audio-based and web-based similarity measures. In Proceedings of the 30th annual international ACM SIGIR conference on research and development in information retrieval (SIGIR 2007). Amsterdam, the Netherlands.
31. P. Knees, M. Schedl, T. Pohle, and G. Widmer Exploring music collections in virtual landscapes IEEE MultiMedia 14 3 2007 46 54 (Pubitemid 47322514)
32. Korst, J.; & Geleijnse, G. (2006). Efficient lyrics retrieval and alignment. In W. Verhaegh, E. Aarts, W. ten Kate, J. Korst, & S. Pauws (Eds.), Proceedings of the 3rd Philips symposium on intelligent algorithms (SOIA 2006) (pp. 205-218). Eindhoven, the Netherlands.
33. P. Lamere Social tagging and music information retrieval Journal of New Music Research: Special Issue: From Genres to Tags: Music Information Retrieval in the Age of Social Tagging 37 2 2008 101 114
34. las (2009). < http://last.fm > Accessed February 2009.
35. Law, E.; von Ahn, L.; Dannenberg, R.; & Crawford, M. (2007). Tagatune: A game for music and sound annotation. In Proceedings of the 8th international conference on music information retrieval (ISMIR 2007). Vienna, Austria.
36. luc (2008). < http://lucene.apache.org > Accessed January 2008.
37. Mandel, M. I.; & Ellis, D. P. (2005). Song-level features and support vector machines for music classification. In Proceedings of the 6th international conference on music information retrieval (ISMIR 2005). London, UK.
38. Mandel, M. I.; & Ellis, D. P. (2007). A web-based game for collecting music metadata. In Proceedings of the 8th international conference on music information retrieval (ISMIR 2007). Vienna, Austria.
39. mys (2008). < http://www.mysql.com > Accessed June 2008.
40. Pachet, F.; Westerman, G.; & Laigre, D. (2001). Musical data mining for electronic music distribution. In Proceedings of the 1st international conference on web delivering of music (WEDELMUSIC 2001). Florence, Italy.
41. Pampalk, E.; & Goto, M. (2007). MusicSun: A new approach to artist recommendation. In Proceedings of the 8th international conference on music information retrieval (ISMIR 2007). Vienna, Austria.
42. Pampalk, E.; Rauber, A.; & Merkl, D. (2002). Content-based organization and visualization of music archives. In Proceedings of the 10th ACM international conference on multimedia (MM 2002) (pp. 570-579). Juan les Pins, France.
43. Pampalk, E.; Flexer, A.; & Widmer, G. (2005). Hierarchical organization and description of music collections at the artist level. In Proceedings of the 9th European conference on research and advanced technology for digital libraries (ECDL 2005). Vienna, Austria.
44. T. Pohle, P. Knees, M. Schedl, E. Pampalk, and G. Widmer Reinventing the wheel: A novel approach to music player interfaces IEEE Transactions on Multimedia 9 2007 567 575 (Pubitemid 46479788)
45. G. Salton, A. Wong, and C.S. Yang A vector space model for automatic indexing Communications of the ACM 18 11 1975 613 620
46. M. Schedl, and T. Pohle Enlightening the sun: A user interface to explore music artists via multimedia content Multimedia Tools and Applications: Special Issue on Semantic and Digital Media Technologies 49 1 2010 101 118
47. Schedl, M.; & Widmer, G. (2007). Automatically detecting members and instrumentation of music bands via web content mining. In Proceedings of the 5th workshop on adaptive multimedia retrieval (AMR 2007). Paris, France.
48. Schedl, M.; Knees, P.; & Widmer, G. (2005a). A web-based approach to assessing artist similarity using co-occurrences. In Proceedings of the 4th international workshop on content-based multimedia indexing (CBMI 2005). Riga, Latvia.
49. Schedl, M.; Knees, P.; & Widmer, G. (2005b). Discovering and visualizing prototypical artists by web-based co-occurrence analysis. In: Proceedings of the 6th International Conference on Music Information Retrieval (ISMIR 2005). London, UK.
50. Schedl, M.; Knees, P.; Pohle, T.; & Widmer, G. (2006). Towards automatic retrieval of album covers. In Proceedings of the 28th European conference on information retrieval (ECIR 2006). London, UK.
51. Schedl, M.; Knees, P.; & Widmer, G. (2006). Investigating web-based approaches to revealing prototypical music artists in genre taxonomies. In Proceedings of the 1st IEEE international conference on digital information management (ICDIM 2006). Bangalore, India.
52. Schedl, M.; Pohle, T.; Knees, P.; & Widmer, G. (2006c). Assigning and visualizing music genres by web-based co-occurrence analysis. In Proceedings of the 7th international conference on music information retrieval (ISMIR 2006). Victoria, Canada.
53. Schedl, M.; Knees, P.; Widmer, G.; Seyerlehner, K.; & Pohle, T. (2007). Browsing the web using stacked three-dimensional sunbursts to visualize term co-occurrences and multimedia content. In Proceedings of the 18th IEEE visualization 2007 conference (Vis 2007). Sacramento, CA, USA.
54. D.J. Sheskin Handbook of parametric and nonparametric statistical procedures 3rd ed. 2004 Chapman & Hall/CRC Boca Raton, London, New York, Washington, DC
55. Stasko, J.; & Zhang, E. (2000). Focus + context display and navigation techniques for enhancing radial, space-filling hierarchy visualizations. In Proceedings of IEEE information visualization 2000. Salt Lake City, UT, USA.
56. Turnbull, D.; Liu, R.; Barrington, L.; & Lanckriet, G. (2007). A game-based approach for collecting semantic annotations of music. In Proceedings of the 8th international conference on music information retrieval (ISMIR 2007). Vienna, Austria.
57. von Ahn, L.; & Dabbish, L. (2004). Labeling images with a computer game. In CHI'04: Proceedings of the SIGCHI conference on human factors in computing systems. New York, NY, USA: ACM Press.
58. Whitman, B.; & Lawrence, S. (2002). Inferring descriptions and similarity for music from community metadata. In Proceedings of the 2002 international computer music conference (ICMC 2002) (pp. 591-598). Göteborg, Sweden.
59. wik (2009). < http://www.wikipedia.org > Accessed December 2009.
60. F. Wilcoxon Individual comparisons by ranking methods Biometrics Bulletin 1 6 1945 80 83
61. Zadel, M.; & Fujinaga, I. (2004). Web services for music information retrieval. In Proceedings of the 5th international symposium on music information retrieval (ISMIR 2004). Barcelona, Spain.
62. J. Zobel, and A. Moffat Inverted files for text search engines ACM Computing Surveys 38 2006 1 56