Ontology-Based Users & Requests Clustering in Customer Service Management System

TL;DR

This paper presents an ontology-based approach for clustering users and requests in customer service management, enhancing semantic interoperability and customization in e-service environments.

Contribution

It introduces a novel ontology-driven method for efficient clustering of users and requests, improving upon traditional data mining techniques.

Findings

Ontology improves semantic understanding between company units and customers.

The approach was successfully tested in an industrial setting.

Enhanced clustering efficiency demonstrated in case studies.

Abstract

Customer Service Management is one of major business activities to better serve company customers through the introduction of reliable processes and procedures. Today this kind of activities is implemented through e-services to directly involve customers into business processes. Traditionally Customer Service Management involves application of data mining techniques to discover usage patterns from the company knowledge memory. Hence grouping of customers/requests to clusters is one of major technique to improve the level of company customization. The goal of this paper is to present an efficient for implementation approach for clustering users and their requests. The approach uses ontology as knowledge representation model to improve the semantic interoperability between units of the company and customers. Some fragments of the approach tested in an industrial company are also presented in the paper.