@inproceedings{27fc960bbfbd4186be46b68149c1081a,
title = "Data Science Approach for crime analysis and prediction: Saudi Arabia use-case",
abstract = "One of the cornerstones of the Saudi Vision 2030 is ensuring a good quality of life. It is closely linked to enhancing security and safety by bolstering ongoing efforts to combat crime by enacting additional measures to ensure road safety, prevent traffic accidents, and lessen the catastrophic effects of such accidents. In our study, we hope to assist authorities in making appropriate judgments on safety and security measures for the benefit of citizens by using crime analysis and predictions. Business Intelligence and machine learning algorithms are used for crime analysis and prediction, respectively. We believe that our approach aids in the production of more reliable crime prevention findings with a 99\% accuracy rate.",
keywords = "analysis, business intelligence, crime, machine learning, prediction, saudi arabia, vision 2030, visualizations",
author = "Nouf Aldossari and Amal Algefes and Fatma Masmoudi and Elham Kariri",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 5th International Conference of Women in Data Science at Prince Sultan University, WiDS-PSU 2022 ; Conference date: 28-03-2022 Through 29-03-2022",
year = "2022",
doi = "10.1109/WiDS-PSU54548.2022.00016",
language = "English",
series = "Proceedings - 2022 5th International Conference of Women in Data Science at Prince Sultan University, WiDS-PSU 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "20--25",
editor = "Tanzila Saba and Jamail, \{Nor Shahida\} and Rabia Latif and Rehman Khan",
booktitle = "Proceedings - 2022 5th International Conference of Women in Data Science at Prince Sultan University, WiDS-PSU 2022",
address = "United States",
}
