Abstract
Digital objects such as images and videos are fundamental resources in digital library. To assist in retrieving such objects usually they are being tagged by some keywords or sentences. The popular approach to tag digital objects is based on associated text. However, relying on associated text alone such as the surrounding text unable to semantically describe such objects. This paper discusses the use of WordNet and ConceptNet to tag digital images beyond terms available in the surrounding text. WordNet is used to disambiguate concepts or terms from the associated text and ConceptNet is meant to infer topics or common-sense knowledge from summarizing the text that describe the images. However, relying on WordNet alone is not sufficed particularly when it comes to disambiguate specific or domain dependent concepts. As such the Name Entity Recognition (NER) technique is required to annotate important entities such as name of a person, location and organization. Our work focused on on-lines news images that are richly described with textual description.
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Noah, S.A., Ali, D.A., Alhadi, A.C., Kassim, J.M. (2010). Going Beyond the Surrounding Text to Semantically Annotate and Search Digital Images. In: Nguyen, N.T., Le, M.T., Świątek, J. (eds) Intelligent Information and Database Systems. ACIIDS 2010. Lecture Notes in Computer Science(), vol 5990. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12145-6_18
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DOI: https://doi.org/10.1007/978-3-642-12145-6_18
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