A Framework for Integrating DBpedia into a Multi-Modality Ontology Image Retrieval

DBpedia provides great opportunities for researchers as a domain concept to enrich resource and information extraction. The integration of DBpedia with ontology-based approach in image retrieval gives complete and rich semantics information to the image. A recent trend in ontology-based image retrieval is to fuse the two basic modalities of images namely textual content (keywords) and visual features, and known as multi-modality ontology. In this paper, the authors present the framework for integrating structured content in DBpedia resources with multi-modality ontology-based image extraction and retrieval system and describe how this framework bridges the semantic gap in content-based image retrieval. The goal is to populate a knowledge base with online image news resources from 12 sport types in the BBC sport news, which has three main items: image, image caption and news information. This system will yield high precision and include diverse sports images for specific entities. A multi-modality ontology retrieval system with complete relational facts about entities will improves the precision of retrieval.