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MIR
2010
ACM
167views Multimedia» more  MIR 2010»
14 years 3 months ago
Improving automatic music classification performance by extracting features from different types of data
This paper discusses two sets of automatic musical genre classification experiments. Promising research directions are then proposed based on the results of these experiments. The...
Cory McKay, Ichiro Fujinaga
NIPS
2007
13 years 10 months ago
Active Preference Learning with Discrete Choice Data
We propose an active learning algorithm that learns a continuous valuation model from discrete preferences. The algorithm automatically decides what items are best presented to an...
Eric Brochu, Nando de Freitas, Abhijeet Ghosh
IJCNLP
2004
Springer
14 years 2 months ago
Combining Labeled and Unlabeled Data for Learning Cross-Document Structural Relationships
Multi-document discourse analysis has emerged with the potential of improving various NLP applications. Based on the newly proposed Cross-document Structure Theory (CST), this pap...
Zhu Zhang, Dragomir R. Radev
BMCBI
2007
173views more  BMCBI 2007»
13 years 8 months ago
Recursive Cluster Elimination (RCE) for classification and feature selection from gene expression data
Background: Classification studies using gene expression datasets are usually based on small numbers of samples and tens of thousands of genes. The selection of those genes that a...
Malik Yousef, Segun Jung, Louise C. Showe, Michael...
KDD
2004
ACM
150views Data Mining» more  KDD 2004»
14 years 9 months ago
Markov Blankets and Meta-heuristics Search: Sentiment Extraction from Unstructured Texts
Extracting sentiments from unstructured text has emerged as an important problem in many disciplines. An accurate method would enable us, for example, to mine online opinions from ...
Edoardo Airoldi, Xue Bai, Rema Padman