Masafumi Hamamoto

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Topic detection is an important subject when voluminous text data is sent continuously to a user. We examine a method to detect topics in text data using feature vectors. Feature vectors represent the main distribution of data and they are obtained by various data analysis methods. This paper examines three methods: singular value decomposition (SVD),(More)
Research Interests Data mining in multimedia and biomedical databases; Video and image classification and retrieval; Pattern and correlation discovery on multimedia, time sequences and graphs; Machine learning techniques for biomedical images and bioinformatics. Refereed Publications (In reverse chronological order. Electronic versions available at:
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