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Ontologies are effective for representing domain concepts and relations in a form of semantic network. Many efforts have been made to import ontology into information matchmaking and retrieval. This trend is further accelerated by the convergence of various high-level concepts and low-level features supported by ontologies. In this paper we propose a comparison between traditional keyword based image retrieval and the promising ontology based image retrieval. To be complete, we construct the ontologies not only on text annotation, but also on a combination of text annotation and image feature. The experiments are conducted on a medium-sized data set including about 4000 images. The result proved the efficacy of utilizing both text and image features in a multi modality ontology to improve the image retrieval.
Wang et al. (Mon,) studied this question.