%0 Conference Proceedings
%T ANOVA Based Approch for Efficient Customer Recognition: Dealing with Common Names
%+ University of New South Wales [Canberra Campus] (UNSW)
%+ University of Tehran
%A Saberi, Morteza
%A Saberi, Zahra
%Z Part 2: Artificial Intelligence for Knowledge Management
%< avec comité de lecture
%( IFIP Advances in Information and Communication Technology
%B 4th IFIP International Conference on Artificial Intelligence in Theory and Practice (AI 2015)
%C Daejeon, South Korea
%Y Tharam Dillon
%3 Artificial Intelligence in Theory and Practice IV
%V AICT-465
%P 64-74
%8 2015-10-04
%D 2015
%R 10.1007/978-3-319-25261-2_6
%K Contact centres
%K Customer recognition
%K Customer common name
%Z Computer Science [cs]Conference papers
%X This study proposes an Analysis of Variance (ANOVA) technique that focuses on the efficient recognition of customers with common names. The continuous improvement of Information and communications technologies (ICT) has led customers to have new expectations and concerns from their related organization. These new expectations bring various difficulties for organizations’ help desk to meet their customers’ needs. In this paper, we propose a technique that provides the most beneficial information to the Customer service representative that will assist in the efficient recognition of the customer. The proposed algorithm determines which features of a customer should be asked that would result in his/her prompt recognition. Moreover, to have a clean database, the framework uses the features of customers for which a standard format is available such as street address, month of birth etc. We evaluate our algorithm on synthetic dataset and demonstrate how we can recognize the right customer in the optimum manner.
%G English
%Z TC 12
%2 https://inria.hal.science/hal-01383957/document
%2 https://inria.hal.science/hal-01383957/file/371690_1_En_6_Chapter.pdf
%L hal-01383957
%U https://inria.hal.science/hal-01383957
%~ IFIP
%~ IFIP-AICT
%~ IFIP-TC
%~ IFIP-TC12
%~ IFIP-AICT-465