Matches in SemOpenAlex for { <https://semopenalex.org/work/W4323046124> ?p ?o ?g. }
Showing items 1 to 99 of
99
with 100 items per page.
- W4323046124 endingPage "161" @default.
- W4323046124 startingPage "161" @default.
- W4323046124 abstract "Increasing internal state security requires an understanding of the factors that influence the commission of repetitive crimes (recidivism) since the crime is not caused by public danger but by the criminal person. Against the background of informatization of the information activities of law enforcement agencies, there is no doubt about the expediency of using artificial intelligence algorithms and blockchain technology to predict and prevent crimes. The prediction machine-learning models for identifying significant factors (individual characteristics of convicts), which affect the propensity to commit criminal recidivism, were applied in this article. For predicting the probability of propensity for criminal recidivism of customers of Ukrainian penitentiary institutions, a Decision Tree model was built to suggest the probability of repeated criminal offenses by convicts. It was established that the number of convictions to the actual punishment and suspended convictions is the main factors that determine the propensity of customers of penitentiary institutions to commit criminal recidivism in the future. Decision Tree models for the classification of convicts prone or not prone to recidivism were built. They can be used to predict new cases for decision-making support in criminal justice. In our further research, the possibility of using the technology of distributed registers/blockchain in predictive criminology will be analyzed." @default.
- W4323046124 created "2023-03-04" @default.
- W4323046124 creator A5006901143 @default.
- W4323046124 creator A5016123191 @default.
- W4323046124 creator A5040752096 @default.
- W4323046124 creator A5045605427 @default.
- W4323046124 creator A5064944037 @default.
- W4323046124 creator A5076836454 @default.
- W4323046124 date "2023-03-03" @default.
- W4323046124 modified "2023-10-01" @default.
- W4323046124 title "Prediction Machine Learning Models on Propensity Convicts to Criminal Recidivism" @default.
- W4323046124 cites W2037076360 @default.
- W4323046124 cites W2097794246 @default.
- W4323046124 cites W2612774508 @default.
- W4323046124 cites W2617118954 @default.
- W4323046124 cites W2625103589 @default.
- W4323046124 cites W2800898900 @default.
- W4323046124 cites W2802009552 @default.
- W4323046124 cites W2912419496 @default.
- W4323046124 cites W2913346170 @default.
- W4323046124 cites W2927380791 @default.
- W4323046124 cites W2946671531 @default.
- W4323046124 cites W2998021954 @default.
- W4323046124 cites W2999303929 @default.
- W4323046124 cites W3007954406 @default.
- W4323046124 cites W3014469142 @default.
- W4323046124 cites W3024261244 @default.
- W4323046124 cites W3046320181 @default.
- W4323046124 cites W3047132612 @default.
- W4323046124 cites W3110521199 @default.
- W4323046124 cites W3119944670 @default.
- W4323046124 cites W3171379815 @default.
- W4323046124 cites W3185180031 @default.
- W4323046124 cites W3190652583 @default.
- W4323046124 cites W3203445419 @default.
- W4323046124 cites W4200017683 @default.
- W4323046124 cites W4200132191 @default.
- W4323046124 cites W4220686723 @default.
- W4323046124 cites W4280525535 @default.
- W4323046124 cites W4283168093 @default.
- W4323046124 cites W4296745153 @default.
- W4323046124 cites W4304814064 @default.
- W4323046124 cites W4304814454 @default.
- W4323046124 cites W596623478 @default.
- W4323046124 doi "https://doi.org/10.3390/info14030161" @default.
- W4323046124 hasPublicationYear "2023" @default.
- W4323046124 type Work @default.
- W4323046124 citedByCount "1" @default.
- W4323046124 countsByYear W43230461242023 @default.
- W4323046124 crossrefType "journal-article" @default.
- W4323046124 hasAuthorship W4323046124A5006901143 @default.
- W4323046124 hasAuthorship W4323046124A5016123191 @default.
- W4323046124 hasAuthorship W4323046124A5040752096 @default.
- W4323046124 hasAuthorship W4323046124A5045605427 @default.
- W4323046124 hasAuthorship W4323046124A5064944037 @default.
- W4323046124 hasAuthorship W4323046124A5076836454 @default.
- W4323046124 hasBestOaLocation W43230461241 @default.
- W4323046124 hasConcept C102587632 @default.
- W4323046124 hasConcept C153180980 @default.
- W4323046124 hasConcept C15744967 @default.
- W4323046124 hasConcept C17744445 @default.
- W4323046124 hasConcept C199539241 @default.
- W4323046124 hasConcept C2776034101 @default.
- W4323046124 hasConcept C2776090404 @default.
- W4323046124 hasConcept C2780262971 @default.
- W4323046124 hasConcept C41008148 @default.
- W4323046124 hasConcept C73484699 @default.
- W4323046124 hasConcept C77088390 @default.
- W4323046124 hasConceptScore W4323046124C102587632 @default.
- W4323046124 hasConceptScore W4323046124C153180980 @default.
- W4323046124 hasConceptScore W4323046124C15744967 @default.
- W4323046124 hasConceptScore W4323046124C17744445 @default.
- W4323046124 hasConceptScore W4323046124C199539241 @default.
- W4323046124 hasConceptScore W4323046124C2776034101 @default.
- W4323046124 hasConceptScore W4323046124C2776090404 @default.
- W4323046124 hasConceptScore W4323046124C2780262971 @default.
- W4323046124 hasConceptScore W4323046124C41008148 @default.
- W4323046124 hasConceptScore W4323046124C73484699 @default.
- W4323046124 hasConceptScore W4323046124C77088390 @default.
- W4323046124 hasIssue "3" @default.
- W4323046124 hasLocation W43230461241 @default.
- W4323046124 hasOpenAccess W4323046124 @default.
- W4323046124 hasPrimaryLocation W43230461241 @default.
- W4323046124 hasRelatedWork W1879755514 @default.
- W4323046124 hasRelatedWork W1995125017 @default.
- W4323046124 hasRelatedWork W2472683612 @default.
- W4323046124 hasRelatedWork W2755138709 @default.
- W4323046124 hasRelatedWork W2788601367 @default.
- W4323046124 hasRelatedWork W2888787938 @default.
- W4323046124 hasRelatedWork W3083183958 @default.
- W4323046124 hasRelatedWork W3155761991 @default.
- W4323046124 hasRelatedWork W4292186353 @default.
- W4323046124 hasRelatedWork W2605941602 @default.
- W4323046124 hasVolume "14" @default.
- W4323046124 isParatext "false" @default.
- W4323046124 isRetracted "false" @default.
- W4323046124 workType "article" @default.