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Utilising semantic technologies for intelligent indexing and retrieval of digital images
Osman, T. Thakker, Dhaval Schaefer, G.
Osman, T.
Thakker, Dhaval
Schaefer, G.
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2014-07
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© 2014 Springer. This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature�s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/s00607-013-0350-0.
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Abstract
The proliferation of digital media has led to a huge interest in classifying and indexing media objects for generic search and usage. In particular, we are witnessing a colossal growth in digital image repositories that are difficult to navigate using free-text search mechanisms, which often return inaccurate matches as they in principle rely on statistical analysis of query keyword recurrence in the image annotation or surrounding text. In this paper we present a semantically-enabled image annotation and retrieval engine that is designed to satisfy the requirements of the commercial image collections market in terms of both accuracy and efficiency of the retrieval process. Our search engine relies on methodically structured ontologies for image annotation, thus allowing for more intelligent reasoning about the image content and subsequently obtaining a more accurate set of results and a richer set of alternatives matchmaking the original query. We also show how our well-analysed and designed domain ontology contributes to the implicit expansion of user queries as well as the exploitation of lexical databases for explicit semantic-based query expansion.
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Osman T, Thakker D and Schaefer G (2014) Utilising semantic technologies for intelligent indexing and retrieval of digital images. Computing. 96(7): 651-668.
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