• Publications
  • Influence
New Algorithms for Fast Discovery of Association Rules
TLDR
New algorithms for fast association mining, which scan the database only once, are presented, addressing the open question whether all the rules can be efficiently extracted in a single database pass. Expand
A comparative study on content-based music genre classification
TLDR
It is demonstrated that the use of DWCHs significantly improves the accuracy of music genre classification and is compared using various machine learning classification algorithms, including Support Vector Machines and Linear Discriminant Analysis. Expand
A comparative study of feature selection and multiclass classification methods for tissue classification based on gene expression
TLDR
It is indicated that multiclass classification problem is much more difficult than the binary one for the gene expression datasets, due to the fact that the data are of high dimensionality and that the sample size is small. Expand
Detecting emotion in music
  • Tao Li, M. Ogihara
  • Computer Science
  • ISMIR
  • 26 October 2003
TLDR
Since the preeminent functions of music are social and psychological, the most useful characterization would be based on four types of information: the style, emotion, genre, and similarity. Expand
Incremental and interactive sequence mining
TLDR
This paper proposes novel techniques for maintaining sequences in the presence of a) database updates, and b) user interaction (e.g. modifying mining parameters). Expand
A survey on wavelet applications in data mining
TLDR
A high-level data-mining framework that reduces the overall process into smaller components is presented that discusses the impact of wavelets on data mining research and outlines potential future research directions and applications. Expand
Using discriminant analysis for multi-class classification: an experimental investigation
TLDR
The experiments suggest that discriminant analysis provides a fast, efficient yet accurate alternative for general multi-class classification problems. Expand
Entropy-based criterion in categorical clustering
TLDR
It is shown that the entropy-based criterion can be derived in the formal framework of probabilistic clustering models and the connection between the criterion and the approach based on dissimilarity co-efficients is established. Expand
Toward intelligent music information retrieval
  • Tao Li, M. Ogihara
  • Computer Science
  • IEEE Transactions on Multimedia
  • 1 June 2006
TLDR
This paper introduces Daubechies Wavelet Coefficient Histograms (DWCH) for music feature extraction for music information retrieval and conducts a proof-of-concept experiment on similarity search using the feature set. Expand
Parallel Algorithms for Discovery of Association Rules
TLDR
This paper describes new parallel association mining algorithms that use novel itemset clustering techniques to approximate the set of potentially maximal frequent itemsets, and presents results on the performance of the algorithms on various databases, and compares it against a well known parallel algorithm. Expand
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