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We considered an original approach for aggregating those individual results to obtain a recommendation from the final output. The preferences are assessed interactively to decrease the cognitive effort of each DM, starting from a small subset of holistic evaluations and expanding the process by incrementing new information in each stage of the model. We also assigned indicators to identify the quality of the results, participation in the individual preferences, and to avoid inconsistencies. We used the model to identify areas that merit more resources to combat crime and employed several criteria that assess types and levels of violence. These results may help policy-makers and planners to draw up and refine public policy interventions in the public security context. <\/jats:p>","DOI":"10.1142\/s0219622019500251","type":"journal-article","created":{"date-parts":[[2019,7,5]],"date-time":"2019-07-05T09:01:59Z","timestamp":1562317319000},"page":"1403-1432","source":"Crossref","is-referenced-by-count":13,"title":["Learning Preferences in a Spatial Multiple Criteria Decision Approach: An Application in Public Security Planning"],"prefix":"10.1142","volume":"18","author":[{"given":"Ciro","family":"Figueiredo","sequence":"first","affiliation":[{"name":"Engineering Department, Federal Rural University of the Semi-arid Region, P.O. Box, 59515-000 Angicos, RN, Brazil"}]},{"given":"Caroline","family":"Mota","sequence":"additional","affiliation":[{"name":"Management Engineering Department, Federal University of Pernambuco, P.O. 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