Abstract
The analysis of video sequences is of primary concern in the field of mass communication. One particular topic is the study of collective visual memories and neglections as they emerged in various cultures, with trans-cultural and global elements (Ludes P., Multimedia und Multi-Moderne: Schlüsselbilder, Fernsehnachrichten und World Wide Web – Medienzivilisierung in der Europäischen Währungsunion. Westdeutscher Verlag, Opladen 2001). The vast amount of visual data from television and web offerings make comparative studies on visual material rather complex and very expensive. A standard task in this realm is to find images that are similar to each other. Similarity is typically aimed at a conceptual level comprising both syntactic as well as semantic similarity. The use of semi-automatic picture retrieval techniques would facilitate this task. An important aspect is to combine the syntactical analysis that is usually performed automatically with the semantic level obtained from annotations or the analysis of captions or closely related text. Association rules are in particular suited to extract implicit knowledge from the data base and to make this knowledge accessible for further quantitative analysis.
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Wilhelm, A.F.X., Jacobs, A., Hermes, T. (2010). Association Rule Mining of Multimedia Content. In: Palumbo, F., Lauro, C., Greenacre, M. (eds) Data Analysis and Classification. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03739-9_21
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