Best resource recommendation for a stochastic process

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dc.contributor.authorThomas, L.
dc.contributor.authorManoj Kumar, M.V.
dc.contributor.authorAnnappa, B.
dc.date.accessioned2026-02-05T09:33:25Z
dc.date.issued2016
dc.description.abstractThe aim of this study was to develop an Artificial Neural Network's recommendation model for an online process using the complexity of load and performance of the resources. The proposed model investigate the resource performance using stochastic gradient decent method and probabilistic cost function for learning ranking function. The test result of CoSeLoG project is presented with accuracy of 72.856%. © 2016 International Information Institute.
dc.identifier.citationInformation, 2016, 19, 10, pp. 4611-4615
dc.identifier.issn13434500
dc.identifier.urihttps://idr.nitk.ac.in/handle/123456789/26091
dc.publisherInternational Information Institute Ltd. No. 509 Fujimi-Cho 6-64-3 Tachikawa City, Tokyo 190-0013
dc.subjectBest resource
dc.subjectCross organization process mining
dc.subjectPolynomial regression model
dc.subjectResource behaviour
dc.titleBest resource recommendation for a stochastic process

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