Can BozdoganA. Nur Zincir-HeywoodIbrahim ZincirZincir-Heywood, A. NurBozdogan, CanZincir, Ibrahim2025-10-0620150218-19401793-640310.1142/S02181940154001972-s2.0-84938842268http://dx.doi.org/10.1142/S0218194015400197https://gcris.yasar.edu.tr/handle/123456789/6916https://doi.org/10.1142/S0218194015400197This research focuses on the identification of relevant experience required for solving IT (Information Technology) problems in small-to medium-sized enterprises. To achieve this we integrated information retrieval techniques with clustering and optimization techniques to design and develop a custom-built Experience Management system for IT management support. We have built and evaluated our system on three different publicly available data sets: Princeton Parallels and GoDaddy. Results support that it is possible to provide the right mix of automation and manual activity for IT experience management while achieving a high accuracy.Englishinfo:eu-repo/semantics/closedAccessIT management, experience management, clustering, optimization, decision supportIT ManagementClusteringExperience ManagementDecision SupportOptimizationArticle