DocumentCode :
2397810
Title :
Inductive Learning of Dispute Scenarios for Online Resolution of Customer Complaints
Author :
Galitsky, Boris A. ; González, María P. ; Chesnevar, C.I.
Author_Institution :
Birkbeck Coll., London Univ.
fYear :
2006
fDate :
Sept. 2006
Firstpage :
103
Lastpage :
108
Abstract :
We focus on online resolution of customer complaints. An efficient way to assist customers and companies is to reuse previous experience with similar agents. A formal representation of customer complaints and a machine learning technique for handling scenarios of interaction between conflicting human agents are proposed. It is shown that analysing the structure of communicative actions without context information is frequently sufficient to advise on complaint resolution strategies. Therefore, being domain-independent, the proposed machine learning technique is a good complement to a wide range of customer response management applications where formal treatment of inter-human interactions is required
Keywords :
customer relationship management; learning by example; customer complaint; customer response management; formal representation; inductive learning; interhuman interactions; machine learning; online resolution; Computer science; Context; Disaster management; Humans; Intelligent systems; Knowledge management; Machine learning; Machinery; Nearest neighbor searches; Traffic control; Customer complaints; Decision Making; Decision Support Systems; Knowledge Management;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Systems, 2006 3rd International IEEE Conference on
Conference_Location :
London
Print_ISBN :
1-4244-01996-8
Electronic_ISBN :
1-4244-01996-8
Type :
conf
DOI :
10.1109/IS.2006.348401
Filename :
4155408
Link To Document :
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