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An ontological framework for media analysis and mining

  • Representation, Processing, Analysis, and Understanding of Images
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Abstract

Advances in tools and technologies for digital media production and analysis have assured the availability of larger and larger amount of data which carry a huge amount of information for solving specific application tasks. This development has stressed the need for advanced systems that are not limited to media storage and management but include also their intelligent representation and retrieval. In this paper, we report current results of an ontological framework under development for mining media data, thus offering the possibility of storing, retrieving, analyzing and investigating media to discover novel knowledge relevant to strategic application processes.

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Authors and Affiliations

  1. Institute of Information Science and Technologies-CNR, Via G. Moruzzi 1, 56124, Pisa, Italy

    S. Colantonio & O. Salvetti

  2. Dorodnicyn Computing Centre of the Russian Academy of Sciences, ul. Vavilova 40, Moscow, Russia

    I. B. Gurevich & Yu. Trusova

Authors
  1. S. Colantonio
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  2. O. Salvetti
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  3. I. B. Gurevich
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  4. Yu. Trusova
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Corresponding author

Correspondence to S. Colantonio.

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Sara Colantonio. MSc degree with honors in computer science, University of Pisa, 2004; PhD student in information engineering at the Department of Information Engineering, Pisa University; temporary researcher at the Institute of Information Science and Technologies, National Research Council, Pisa. Received a grant from Finmeccanica for studies in the field of image categorization with applications in medicine and quality control. Her main interests include neural networks, machine learning, industrial diagnostics, and medical imaging. Coauthor of more than 30 scientific papers. Currently involved in a number of European research projects regarding image mining, information technology, and medical decision support systems.

Igor B. Gurevich. Born 1938. Dr. Eng. (Diploma Engineer (Automatic Control and Electrical Engineering), 1961, Moscow Power Engineering Institute, Moscow, USSR); Dr. (Theoretical Computer Science/Mathematical Cybernetics), 1975, Moscow Institute of Physics and Technology, Moscow, USSR. Head of department at the Dorodnicyn Computing Center of the Russian Academy of Sciences, Moscow; assistant professor at the Faculty of Computer Science, Moscow State University. Since 1960, has worked as an engineer and researcher in industry, medicine, and universities and in the Russian Academy of Sciences. Area of expertise: image analysis; image understanding; mathematical theory of pattern recognition; theoretical computer science; pattern recognition and image analysis techniques for applications in medicine, nondestructive testing, and process control; knowledge bases; knowledge-based systems. Two monographs (in coauthorship); 135 papers on pattern recognition, image analysis, and theoretical computer science and applications in peer-reviewed international and Russian journals and conference and workshop proceedings; one patent of the USSR and four patents of the RF. Executive secretary of the Russian Association for Pattern Recognition and Image Analysis, member of the governing board of the International Association for Pattern Recognition (representative from the Russian Federation), IAPR fellow. Has served as PI of many research and development projects as part of national research (applied and basic) programs of the Russian Academy of Sciences, the Ministry of Education and Science of the Russian Federation, the Russian Foundation for Basic Research, the Soros Foundation, and INTAS. Deputy editor in chief of Pattern Recognition and Image Analysis.

Ovidio Salvetti. Director of research at the Institute of Information Science and Technologies (ISTI), National Research Council (CNR), Pisa. Working in the field of theoretical and applied computer vision. His fields of research are image analysis and understanding, pictorial information systems, spatial modeling, and intelligent processes in computer vision. Coauthor of four books and monographs and more than 300 technical and scientific articles, with ten patents regarding systems and software tools for image processing. Has served as a scientific coordinator of several national and European research and industrial projects; in collaboration with Italian and foreign research groups, in the fields of computer vision and high-performance computing for diagnostic imaging. Member of the editorial boards of the international journals Pattern Recognition and Image Analysis and G. Ronchi Foundation Acts. Currently the CNR contact person in ERCIM (the European Research Consortium for Informatics and Mathematics) for the Working Group on Vision and Image Understanding and a member of IEEE and of the steering committee of a number of EU projects. Head of the ISTI Signals and Images Laboratory.

Yulia O. Trusova. Born 1980. Graduated from the Faculty of Computational Mathematics and Cybernetics of Lomonosov Moscow State University in 2002. Works at the Dorodnicyn Computing Center of the Russian Academy of Sciences. Scientific interests: mathematical theory of pattern recognition and image analysis, methods of discrete mathematics, databases and knowledge bases, and computational linguistics. Coauthor of more than 25 papers. Laureate of the Aspirant Award, 2003–2005. Member of the Russian Association for Pattern Recognition and Image Analysis.

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Colantonio, S., Salvetti, O., Gurevich, I.B. et al. An ontological framework for media analysis and mining. Pattern Recognit. Image Anal. 19, 221–230 (2009). https://doi.org/10.1134/S1054661809020023

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