Improving prototypical artist detection by penalizing exorbitant popularity

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3902 LNCS, Issue , 2006, Pages 196-200

  Schedl, Markus ^a,b   Knees, Peter ^a   Widmer, Gerhard ^a,b  

^a JOHANNES KEPLER UNIVERSITY LINZ   (Austria)

^b AUSTRIAN RESEARCH INSTITUTE FOR ARTIFICIAL INTELLIGENCE   (Austria)

Author keywords

[No Author keywords available]

Indexed keywords

DATA PROCESSING; DATA REDUCTION; DATABASE SYSTEMS; MATRIX ALGEBRA; SPEECH ANALYSIS; WEBSITES;

CO-OCCURRENCE ANALYSIS; GENRES; PENALIZATION FUNCTION; PROTOTYPICALITY;

COMPUTER MUSIC;

EID: 33745712271     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11751069_18     Document Type: Conference Paper

References (4)

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2. G. Salton and C. Buckley. Term-weight ing approaches in automatic text retrieval. Information Processing and Management, 24(5):513-523, 1988.
3. M. Schedl, P. Knees, and G. Widmer. A Web-Based Approach to Assessing Artist Similarity using Co-Occurrences. In Proc. of the 4th International Workshop on Content-Based Multimedia Indexing, Riga, Latvia, June 2005.
4. M. Schedl, P. Knees, and G. Widmer. Discovering and Visualizing Prototypical Artists by Web-based Co-Occurrence Analysis. In Proc. of the 6th International Conference on Music Information Retrieval, London, UK, September 2005.