Détails Publication
Data Search in Smart GIS Database Using Map Reduce Pattern and Bayesian Probability,
Discipline: Informatique et sciences de l'information
Auteur(s): Moubaric Kabore, Abdoulaye Sere and Vini Yves Bernadin Loyara
Auteur(s) tagués: LOYARA Vini Yves Bernadin
Renseignée par : LOYARA Vini Yves Bernadin
Résumé

This paper deals with Bayesian approach in Data Research in GIS database through artificial Intelligence (AI) modules, reading the best bayesian probability before returning the data requested, denoted AI4DB. The proposed method combines meshing techniques and the map-reduce algorithm with Bayesian approach to obtain a smart GIS database to reduce the execution time. According to the values of the Bayesian probability, the nearest sites of any position resulting of the user requests, are extracted speedily from the database using the map reduce framework. The execution time is less than the time for the case of the classical method, based only on a parallelism search without a probability. Only a map function with the best bayesian probability for the data in entry, executes entirely its instruction.

Mots-clés

MapReduce, GIS, Bayesian Probability

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