Ontology-based Dynamic Semantic Annotation for Social Image Retrieval

To mitigate the semantic gap between a visual feature and linguistic representation in social image retrieval, researchers have proposed an automatic image annotation approach, which employs multiple visual features and text matching to label images. This paper used a linked open data approach and ontology to construct a model, an automatic semantic image annotation model for social image retrieval. These models enable users to label images through automatic semantic annotation and to identify the underlying intents of semantics, thereby fulfilling user needs and enhancing the retrieval accuracy.