Domain-Oriented Subject Aware Model for Multimedia Data Retrieval

With the increment of the scale of internet information as well as the cross-correlation interaction, how to achieve accurate retrieval of multimedia data is an urgent question in terms of efficiently utilizing information resources. However, existing information retrieval approaches provide only limited capabilities to search multimedia data. In order to improve the ability of information retrieval, we propose a domain-oriented subject aware model by introducing three innovative improvements. Firstly, we propose the text-image feature mapping method based on the transfer learning to extract image semantics. Then we put forward the annotation document method to accomplish simultaneous retrieval of multimedia data. Lastly, we present subject aware graph to quantify the semantics of query requirements, which can customize query threshold to retrieve multimedia data. Conducted experiments show that our model obtained encouraging performance results.