Current Proceedings on Technology

Yazarlar: Nazir Hawi

Konular:-

Anahtar Kelimeler:Artificial intelligence,Expert system,Data mining,Visual c#,Programming,Weka,Interface,Intelligent agent,Machine learning,Classification,Bayesian networks.

Özet: This research presents the design, development, and implementation of a practical and specialized expert system built with Visual C# called IAES. It is constructed to 1) replace human expert diagnosis of Internet addiction, to suggest ways of gradual remedy for Internet addicts until they are diagnosed as Internet non-addicts, and 3) follow up by checking individual’s progress. IAES’ primary function is to take input from a human user based on which it reports the person’s Internet addiction level using the data mining software WEKA. In the finding of a pathognomonic sign, IAES offers users the choice of adding to the output suggestions that can change their behavior in order to help them withdraw from Internet addiction. This can be achieved using Young’s IAT cutoffs. The complete report is saved upon the user’s request in a non-embedded database server for future reference. Furthermore, stored data can be used to interpret users’ progress by comparing the most recent previous results with those of subsequent tests. Also, individual cases can be garnered into WEKA’s data source file. This addition enables the expert system to be truly intelligent since it empowers its learning capability. IAES is a real time multi-layer application with stable code, clear logic, and growing data source.

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