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Police Data Mining and Classification Based on PDCSC Algorithm in International Police Cooperation

Published: 20 September 2024 Publication History

Abstract

Abstract. Aiming at the problems of low data collaboration rate and weak storage capacity of police surveillance data in national border police cooperation, the research is based on Parallel Distributed Clustering with Semantic Constraints (PDCSC) algorithm. Police surveillance data processing model is constructed. The research firstly utilizes local density clustering algorithm to mine and classify the surveillance data, and then introduces the concept of parallelism and constructs the processing model using PDCSC algorithm. The results show that the clustering purity of police surveillance data based on PDCSC method is 92.37% and the data clustering accuracy is 93.67%. Meanwhile, the surveillance data summary of PDCSC method is 7108 which is 1085 and 2241 higher than that of DBSCAN and K-means. This indicates that the PDCSC algorithm can effectively process and classify police surveillance data, providing accurate police incident identification and analysis. The research aims to provide strong support for international police cooperation and improve the efficiency and accuracy of police work.

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        FAIML '24: Proceedings of the 2024 3rd International Conference on Frontiers of Artificial Intelligence and Machine Learning
        April 2024
        379 pages
        ISBN:9798400709777
        DOI:10.1145/3653644
        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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        Publication History

        Published: 20 September 2024

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        Author Tags

        1. Data classification
        2. Data mining
        3. International police cooperation
        4. PDCSC algorithm
        5. Surveillance data

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