Establishing Correspondences between Attribute Spaces and Complex Concept Spaces Using Meta-PGN Classifier
DOI:
https://doi.org/10.55630/dipp.2012.2.28Keywords:
Multimedia Semantics, Metadata, Data Mining, Pattern Recognition, Classification, Categorization, Content-Based Image Retrieval (CBIR)Abstract
In this paper, we present one approach for extending the learning set of a classification algorithm with additional metadata. It is used as a base for giving appropriate names to found regularities. The analysis of correspondence between connections established in the attribute space and existing links between concepts can be used as a test for creation of an adequate model of the observed world. Meta-PGN classifier is suggested as a possible tool for establishing these connections. Applying this approach in the field of content-based image retrieval of art paintings provides a tool for extracting specific feature combinations, which represent different sides of artists' styles, periods and movements.References
Agrawal R: Narrowing Down the Semantic Gap between Content and Context Using Multimodal Keywords. PhD thesis, Wayne State University ( )
Castelli, V., Bergman, D. (eds.): Image Databases: Search and Retrieval of Digital Imagery, John Wiley & Sons (2002)
Chen, C.-C., Wactlar, H., Wang, J., Kiernan, K.: Digital imagery for significant cultural and historical materials – An emerging research field bridging people, culture, and technologies, Int. J. Digital Libraries 5(4), 275-286 (2005)
Croft, W.: What Do People Want from Information Retrieval? (The Top 10 Research Issues for Companies that Use and Sell IR Systems), Centre for Intelligent Information Retrieval Computer Science Department, University of Massachusetts, Amherst (1995)
Datta, R.: Semantics and Aesthetic Inference for Image Search: Statistical Learning Approaches, PhD thesis, Pennsylvania State University (2009)
Ivanova, Kr., Mitov, I. Markov, Kr., Stanchev, P., Vanhoof, K., Aslanyan, L., Sahakyan, H.: Metric categorization relations based on support system analysis, Proc. of the 7th Int. Conf. "Computer Science and Information Technologies", Yerevan, Armenia, 85-88 (2009)
Ivanova, Kr., Stanchev, P., Dimitrov, B.: Analysis of the distributions of color characteristics in art painting images, Serdica J. of Computing, 2(2), 101-126 (2008)
Ivanova, Kr., Stanchev, P., Vanhoof, K.: Automatic tagging of art images with color harmonies and contrasts characteristics in art image collections, Int. J on Advances in Software, 3(3&4), 474-484 (2010)
Mitov, I., Ivanova, Kr., Markov, Kr., Velychko, V., Vanhoof, K., Stanchev, P.: PaGaNe – A classification machine learning system based on the multidimensional numbered information spaces, Proc. of 4th Int. Conf. "Intelligent Systems and Knowledge Engineering" (ISKE 2009), Hasselt, Belgium, Printed in World Scientific Proceedings Series on Computer Engineering and Information Science, No:2, 279-286 (2009)
Scherp, A. Jain, R.: Towards an ecosystem for semantics, Proc. of First ACM Workshop on the Many Faces of Multimedia Semantics (MS'07), 3-11 (2007)
Smeulders, A., Worring, M., Santini, S., Gupta, A., Jain, R.: Content based image retrieval at the end of the early years, IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(12), 1349-1380 (2000)
Wagner, H.: Begriff, Handbuch Philosophischer Grundbegriffe, München, 191 -209 (1973)
Wille, R.: Concept lattices and conceptual knowledge systems, Int. J. "Computers and Mathematics with Applications", 23(6-9), 493-515 (1992)