Abstract
The primary aim of this research project is to develop a generic framework and methodologies that will enable the augmentation of expert knowledge with knowledge extracted from multimedia sources such as text and pictures, for the purpose of classification and analysis. For evaluation and testing purposes of this research study, a furniture design style domain is selected because it is a common belief that design style is an intangible concept that is difficult to analyze. In this paper, we present the results of the analysis of keywords in the text descriptions of design styles. A simple keyword-based matching technique is used for classification and domain specific dictionaries of keywords are used to reduce the dimensionality of feature space. A comparative evaluation was carried out for this classifier and SVM and decision tree based classifier C4.5
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© 2003 Springer-Verlag Berlin Heidelberg
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Lorensuhewa, A., Pham, B., Geva, S. (2003). Style Recognition Using Keyword Analysis. In: Zaïane, O.R., Simoff, S.J., Djeraba, C. (eds) Mining Multimedia and Complex Data. PAKDD 2002. Lecture Notes in Computer Science(), vol 2797. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39666-6_17
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DOI: https://doi.org/10.1007/978-3-540-39666-6_17
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-20305-6
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