Research Article
A Survey on the Profiles of Drug-related Cases and their Depiction
@INPROCEEDINGS{10.4108/eai.26-5-2023.2337241, author={Chengling Huang and Mingzhi Huang and Fu Liao and Huang Liang and Zhen Zhang and Xiaojian Li and Jinw Nong}, title={A Survey on the Profiles of Drug-related Cases and their Depiction}, proceedings={Proceedings of the 4th International Conference on Education, Knowledge and Information Management, ICEKIM 2023, May 26--28, 2023, Nanjing, China}, publisher={EAI}, proceedings_a={ICEKIM}, year={2023}, month={9}, keywords={incident profile incident depiction neural network machine learning}, doi={10.4108/eai.26-5-2023.2337241} }- Chengling Huang
Mingzhi Huang
Fu Liao
Huang Liang
Zhen Zhang
Xiaojian Li
Jinw Nong
Year: 2023
A Survey on the Profiles of Drug-related Cases and their Depiction
ICEKIM
EAI
DOI: 10.4108/eai.26-5-2023.2337241
Abstract
An important direction in the field of computer science research is computer application technology research. For example, how to use advanced deep learning technology to process crime big data to quickly assist in the detection of drug-related cases. Profile of criminal case is important intelligence for investigation. It should be a whole that constitutes a set of distinctive features such as the features of things, the characteristics of people, and the relations between them. This paper surveys on the profiles and their depiction methods in recent research. Those studies focus on spatiotemporal features of incidents such as personal security for travel, invasion of property, and fraud. However, other features, such as motives, processes, suspects and results, are also important for the investigation to drug-related complex cases. A taxonomy of the profiles and their depiction methods is given. We point out the problems: the studies didn't integrally focus on understanding and representing these features and their investigative experiences, and mostly characterize case features with their non-fully connected neural network-oriented data types. Meanwhile, the suggestions are proposed for the profiles of drug-related cases and their description.