Style Recognition using Keyword Analysis

Lorensuhewa, Aruna, Pham, Binh L., & Geva, Shlomo (2003) Style Recognition using Keyword Analysis. In Zaiane, Osmar R., Simoff, Simeon J., & Djeraba, Chabane (Eds.) Lecture Notes in Artificial Intelligence; Mining Multi-Media and Complex Data, Springer, pp. 266-280.

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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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ID Code: 2029
Item Type: Conference Paper
Refereed: Yes
Additional Information: Author contact details :
Keywords: Knowledge Extraction, Text Retrieval, Text Categorization, Support Vector Machine, Decision Trees, Data Mining, C4, 5, Design Style
DOI: 10.1007/b12031
ISBN: 9783540203056
ISSN: 1611-3349
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > LIBRARY AND INFORMATION STUDIES (080700) > Information Retrieval and Web Search (080704)
Divisions: Current > QUT Faculties and Divisions > QUT Business School
Past > QUT Faculties & Divisions > Faculty of Science and Technology
Copyright Owner: Copyright 2003 Springer
Copyright Statement: This is the author-version of the work. Conference proceedings published, by Springer Verlag, will be available via SpringerLink. Lecture Notes in Computer Science
Deposited On: 10 Feb 2006 00:00
Last Modified: 29 Feb 2012 12:58

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