Data mining technique to analyse and predict crime using crime categories and arrest records

Khatun, Most. Rokeya; Ayon, Safial Islam; Hossain, Rahat; Alam, Md. Jaber

doi:10.11591/ijeecs.v22.i2.pp1052-1060

Cited by 7 publications

(6 citation statements)

References 11 publications

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“…At different stages of human social development, the emphasis and inclination of legal protection are also different. In contemporary times, the society is full of various dangers, and the safety of public life and property is increasingly valued and protected, so the application of data mining technology to the law is of great significance [2]. Especially in the context of today's risk society, harmful behaviors against the public are increasing, and necessary measures should be taken in a timely manner for some behaviors that pose a major threat to public security interests and have serious social harm.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Legal Issues of the Crime of Endangering Public Safety Based on Data Mining Algorithm

Feng

2022

Security and Communication Networks

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In order to improve the analysis effect of legal issues of the crime of endangering public safety, this paper analyzes the legal issues of the crime of endangering public safety based on the actual mining algorithm and uses numerical methods to qualitatively study the evolution behavior across phase intervals. Moreover, this paper improves the algorithm based on the actual needs of legal mining. When solving the eigenvalues of the given Hamiltonian’s duration equation, the zero-energy solution can be found in the case of open boundaries. In addition, this paper applies the improved algorithm proposed in this paper to the mining of criminal law legal issues of crimes against public safety, assigns a dynamic IP to each process, and builds a model based on this. Through the above simulation research, it can be seen that the legal problem analysis model of the crime of endangering public safety based on the data mining algorithm proposed in this paper has a good legal data mining effect.

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Section: Introductionmentioning

confidence: 99%

Analysis of Legal Issues of the Crime of Endangering Public Safety Based on Data Mining Algorithm

Feng

2022

Security and Communication Networks

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“…They also proved that any empirical data on crime is compatible with criminological theories and suggested that the prediction accuracy of the stacking ensemble model is higher than that of the individual. (Khatun et al, 2021) gave an idea of how crime investigation agencies can utilize data mining to discover relevant precautionary measures from prediction rates using some supervised classification algorithms, namely decision trees, KNN, and random forest algorithms. It focused on forecasting the crime for frequently occurring crimes like robbery, assault, and theft, and test data showed random forest gives the highest accuracy.…”

Section: Related Workmentioning

confidence: 99%

Comprehensive analysis of Classical Machine Learning models and Ensemble methods for predicting Crime in urban society

Divyasri¹,

Saranya

P.Kathiravan

2023

Preprint

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Crimes are a social issue that affects not only an individual but also humanity. Crime classification techniques for crime forecasting are an emerging research area. generally, Crime data are centrally organized with regular maintenance of the criminal registers that can aid officers in sharing observations and improve early alert approaches to keep the citizens secure within their towns. Hence, the aim of this study is to compare the performance of the state-of-the-art Dynamic Ensemble Selection of Classifier algorithms for predicting crime. We used five different benchmark crime datasets (Chicago, San Francisco, Pheonix, Boston, and Vancouver) for this experimental research work. The performance of the state-of-the-art dynamic ensemble selection of classifiers algorithms was evaluated and compared using various performance evaluation metrics such as accuracy, F1-score, precision, and recall. The KNORA Dynamic ensemble algorithms, which select the subset of ensemble members before the forecasting, outperformed the typical machine learning algorithms, and also the traditional ensemble algorithm techniques in terms of accuracy showed that the dynamic ensemble algorithms are more powerful. This ability to predict crimes within urban societies can help citizens, and law enforcement makes precise informed conclusions and preserves the neighborhoods more unassailably to improve the quality of life for humans.

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“…POS tags can be used to differentiate words and articulate their speech parts. The Lemmatization process relies mainly on POS tagging [19].…”

Section: Part Of Speech Taggingmentioning

confidence: 99%

Naïve-Bayes family for sentiment analysis during COVID-19 pandemic and classification tweets

Ressan

Hassan

2022

IJEECS

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This paper proposes a system to analyze the sentiments of tweeters. It is to build an accurate model to detect different emotions in a tweet. The analysis takes place through several stages (i.e., pre-processing, feature extraction, and training more than one machine learning (ML)). Naïve Bayes, Multinomial Naïve Bayes and Bernoulli Naïve Bayes were selected as supervised machine learning for sentiment analysis using a dataset of 3,057 tweets with users ranging from fear to happiness, anger, and sadness because this method is suitable for solving a problem of this type. This system was also applied to another dataset of 10,000 Tweets (5,000 positive and 5,000 negatives). This approach, consisting of three Naïve Bayes classification models, was applied to two datasets to analyze the sentiment used in them and classify each category separately. The Multinomial Naïve Bayes model outperformed the other models Where it achieved an accuracy of (91.6%) when applied to the first dataset and accuracy (87.6%) when applied to the second dataset. The researchers aim to continue this research with larger data by using other methods of sentiment analysis to predict users' thoughts about COVID-19 or any other problem and to obtain higher accuracy for the models used.

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Data mining technique to analyse and predict crime using crime categories and arrest records

Cited by 7 publications

References 11 publications

Analysis of Legal Issues of the Crime of Endangering Public Safety Based on Data Mining Algorithm

Analysis of Legal Issues of the Crime of Endangering Public Safety Based on Data Mining Algorithm

Comprehensive analysis of Classical Machine Learning models and Ensemble methods for predicting Crime in urban society

Naïve-Bayes family for sentiment analysis during COVID-19 pandemic and classification tweets

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