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003 | AR-LpUFIB | ||
005 | 20250311170511.0 | ||
008 | 230201s2021 xx o 000 0 spa d | ||
024 | 8 |
_aDIF-M8352 _b8572 _zDIF007644 |
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_aAR-LpUFIB _bspa _cAR-LpUFIB |
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100 | 1 | _aMartínez, Victor | |
245 | 1 | 0 | _aProcess mining applied to postal distribution |
300 | _a1 archivo (355,2 kB) | ||
500 | _aFormato de archivo PDF. -- Este documento es producción intelectual de la Facultad de Informática - UNLP (Colección BIPA/Biblioteca) | ||
520 | _aProcess mining is a technique that allows analyzing business processes through event logs. In this article, different process mining techniques are used to analyze data based on the postal distribution of products in the Argentine Republic between the years 2017 and 2019. The results obtained allow stating that 85% of the shipments made conform exactly to the model. The analysis of the situations with a low level of adjustment to the discovered process constituted a tool for quick identification of some recurring problems in the distribution, facilitating the analysis of the deviations that occurred. In the future, we expect to incorporate these techniques to build early notifications that warn about the existence of excessive deviations from the process | ||
534 | _aCongreso Argentino de Ciencias de la Computación (27mo : 2021 : Salta, Argentina) | ||
650 | 4 | _aMINERÍA DE DATOS | |
650 | 4 | _aGESTIÓN DE PROCESOS EMPRESARIALES - BPM | |
653 | _aminería de procesos | ||
653 | _adistribución postal | ||
700 | 1 | _aLanzarini, Laura Cristina | |
700 | 1 | _aRonchetti, Franco | |
856 | 4 | 0 | _uhttp://sedici.unlp.edu.ar/handle/10915/130342 |
942 | _cCP | ||
999 |
_c57417 _d57417 |