INVESTIGADORES
CHESÑEVAR Carlos Ivan
artículos
Título:
A Novel Approach for Classifying Customer Complaints through Graphs Similarities in Argumentation Dialogues
Autor/es:
BORIS GALITSKY; MARÍA PAULA GONZÁLEZ; CARLOS IVÁN CHESÑEVAR
Revista:
DECISION SUPPORT SYSTEMS
Editorial:
Elsevier
Referencias:
Lugar: Amsterdam; Año: 2009 vol. 46 p. 717 - 729
ISSN:
0167-9236
Resumen:
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 scenarios associated with customer-company dialogues. Such dialogues are formalized as labelled graphs, in 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.
