Ismail M.N.Torkey F.A.Ali K.A.M.Faculty of Electronic EngineeringDept. of Comp. Sci. and EngineeringMenoufia UniversityMenouf 32952Egypt; Faculty of Computers and InformationMenoufia UniversityShebin El KomEgypt; MSA UniversityCairoDokkiEgypt2020-01-252020-01-252004780385756https://ieeexplore.ieee.org/document/1374402ScopusThis paper applies the concept of the application server, three-tier architecture, EJB, and J2EE to knowledge discovery in large databases which is using the letter recognition classification and detection as an example case. EJBs will be used as intermediate connecting layer, also called middle tier, to get requests from the clients and pass the request to database server. Cloud-scape or Oracle9i database server will provide database support and JDBC (thin) for cloudscape or Oracle9i that work on Windows NT/2000/XP environment will provide database connection. We show how a classification metric drawn from Rule-Induction/Decision Tree algorithms can be computed via the Java model. Performance evaluation figures, such as classification error rate and number of rules, are presented for adaptive data mining classifiers and filters, using the Letter Image Recognition Data example which is the practical implementation of this work. 2004 IEEE.EnglishApplication serverData miningEJBJ2EE platformRule-Induction/Decision Tree classifier algorithmsScalabilitySecurityThree-tier client-serverAdaptive filteringAlgorithmsClassification (of information)Client server computer systemsComputer architectureData miningDatabase systemsSecurity of dataServersTrees (mathematics)Adaptive data mining classifiersApplication serversEJBJ2EE platformRule-induction/decision tree classifier algorithmsScalabilityThree-tier client-serverInterfaces (computer)Conference Paper