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Abstract

This paper centres on the tools for the management of new digital documents, which are not only textual, but also visual-video, audio or multimedia in the full sense. Among the aims is to demonstrate that operating within the terms of generic Information Retrieval through textual language only is limiting, and it is instead necessary to consider ampler criteria, such as those of MultiMedia Information Retrieval, according to which, every type of digital document can be analyzed and searched by the proper elements of language for its proper nature. MMIR is presented as the organic complex of the systems of Text Retrieval, Visual Retrieval, Video Retrieval, and Audio Retrieval, each of which has an approach to information management that handles the concrete textual, visual, audio, or video content of the documents directly, here defined as content-based. In conclusion, the limits of this content-based objective access to documents is underlined. The discrepancy known as the semantic gap is that which occurs between semantic-interpretive access and content-based access. Finally, the integration of these conceptions is explained, gathering and composing the merits and the advantages of each of the approaches and of the systems to access to information.

Footnote

Bezugnahme auf: Enser, P.G.B.: Visual image retrieval. In: Annual review of information science and technology. 42(2008), S.3-42.