Data mining for customer service support

In this thesis, the related work on data mining functions, techniques and tools are first reviewed. Text mining techniques and some of the common data mining applications are then discussed. Techniques in decision support and intelligent fault diagnosis are also reviewed. As the customer service database is used for mining, the details of various tables of the database are described. A data mining process using the DBMiner system is proposed to mine the structured data from the customer service database for decision support. The data mining process starts with establishing the mining goals. The data tables that are suitable for mining are then selected and pre-processed to eliminate irrelevant or noisy data. The pre-processed data are transformed to a suitable form and stored into a data warehouse. The data mining functions including summarization, association, classification, prediction and clustering are then performed. Finally, the results of the mining functions are evaluated.Master of Applied Scienc