Using Supervised Clustering Technique to Classify Received Messages in 137 Call Center of Tehran City Council

Supervised clustering is a data mining technique that assigns a set of data topredefined classes by analyzing dataset attributes. It is considered as an importanttechnique for information retrieval, management, and mining in informationsystems. Since customer satisfaction is the main goal of organizations in modernsociety, to meet the requirements, 137 call center of Tehran city council is planningto reduce the waiting time of customers, forwarding their messages to theappropriate service manager to increase service quality. The city council iscurrently using a manual approach dispatching textual request messages. Since thisprocess is very similar to supervised clustering concept, in this study, we applied theNaïve Bayes algorithm, which is one of the most common algorithms in thesupervised clustering arena to classify received messages regarding their subjects.The performance results of the proposed technique indicate its high efficiency inclustering the received messages with 98% accuracy.

Keywords:

supervised clustering , classification , Naïve Bayes algorithm , data mining