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Multimedia information retrieval (MMIR or MIR) is a research discipline of computer science that aims at extracting semantic information from multimedia data sources.[1][failed verification] Data sources include directly perceivable media such as audio, image and video, indirectly perceivable sources such as text, semantic descriptions,[2] biosignals as well as not perceivable sources such as bioinformation, stock prices, etc. The methodology of MMIR can be organized in three groups:
Methods for the summarization of media content (feature extraction). The result of feature extraction is a description.
Methods for the filtering of media descriptions (for example, elimination of redundancy)
Methods for the categorization of media descriptions into classes.
^H Eidenberger. Fundamental Media Understanding, atpress, 2011, p. 1.
^Sikos, L. F. (2016). "RDF-powered semantic video annotation tools with concept mapping to Linked Data for next-generation video indexing: a comprehensive review". Multimedia Tools and Applications. 76 (12): 14437–14460. doi:10.1007/s11042-016-3705-7. S2CID 254832794.
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