A novel approach for classifying customer complaints through graphs similarities in argumentative dialogues

作者：Galitsky Boris A; Gonzalez Maria P; Chesnevar Carlos I^*

来源：Decision Support Systems, 2009, 46(3): 717-729.

DOI：10.1016/j.dss.2008.11.015

• Automated decision making
• Automated complaint processing
• Argumentative dialogues
• Pattern matching

Automating customer complaints processing is a major issue in the context of knowledge management technologies for most companies nowadays. Automated decision-support systems are important for complaint processing, integrating human experience in understanding complaints and the application of machine learning techniques. In this context, a major challenge in complaint processing involves assessing the validity of a customer complaint on the basis of the emerging dialogue between a customer and a company representative. This paper presents a novel approach for modelling and classifying complaint-company dialogues. Such dialogues are formalized as labelled graphs, in scenarios associated with customer which both company and customer interact through communicative actions, providing arguments that support their points. We show that such argumentation provides a complement to perform machine learning reasoning on communicative actions, improving the resulting classification accuracy.

• 出版日期2009-2