Abstract
With the development of information technology, electronic data cues have been playing an important role in the investigation of criminal cases. However, the difficulty of analyzing massive data have also brought great challenges to criminal investigations. At present, Big data, artificial intelligence and other technologies are used to store and analyze electronic evidence such as text, pictures, videos, forms, etc. However, to deeply mine and make full use of the semantic information of evidence and to break the barrier between various heterogeneous data are still hard to be settled. To solve these problems, the innovation of storage form of data is desperately needed to construct a unified expression of data for heterogeneous information. This paper proposes to build a case-oriented knowledge graph, and provides solutions to the association and the relation of the knowledge graph with external information and non-electronic data evidence respectively. This knowledge graph can be used to realize the reasoning and judgment of cross-structure information, and assist the public security organs to detect cases.
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Acknowledgments.
This work was supported in part by Guangdong Province Key Research and Development Plan (Grant No. 2019B010137004), the National Key research and Development Plan (Grant No. 2018YFB1800701, No. 2018YFB0803504, and No. 2018YEB1004003), and the The National Natural Science Foundation of China (Grant No. U1636215 and 61572492).
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Wu, H. (2019). Research on Electronic Evidence Management System Based on Knowledge Graph. In: Wang, G., Bhuiyan, M.Z.A., De Capitani di Vimercati, S., Ren, Y. (eds) Dependability in Sensor, Cloud, and Big Data Systems and Applications. DependSys 2019. Communications in Computer and Information Science, vol 1123. Springer, Singapore. https://doi.org/10.1007/978-981-15-1304-6_33
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DOI: https://doi.org/10.1007/978-981-15-1304-6_33
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