No abstract

With the advent of the era of big data, the Provenance Method of electronic archives based on knowledge graph under the environment of big data has produced a large number of electronic archives due to the development of science and technology. How to guarantee the credential characteristics of electronic archives in the big data environment has attracted wide attention of the academic community. Provenance is an important technical means to guarantee the certification of electronic archives. In this paper, knowledge graph technology is used to provide the concept provenance of electronic archives in large data environment. It not only enriches the provenance method, but also guarantees the certification of electronic archives in the large data environment.

As a large number of the multimedia information emerges, the cross-media retrieval system becomes an important research focus. The cross-media retrieval system is based on the traditional content retrieval, extracting color, texture, and shape features vector of the images. A new method was carried out in this paper. Firstly, the uniform semantic representational framework was built to organize the different mode media heterogeneous characteristics. Secondly, the Ontology database representing each type of media concepts was set up. The Ontology database organizes the low level features of the multimedia objects to associate multimedia files in the semantic level. Thirdly, the cross-media retrieval algorithm based on ontology was introduced. The results of the experiment showed that this cross-media retrieval method based on the Ontology was more effective and accurate.