Context Analysis of Customer Requests using a Hybrid Adaptive Neuro Fuzzy Inference System and Hidden Markov Models in the Natural Language Call Routing Problem

Context Analysis of Customer Requests using a Hybrid Adaptive Neuro Fuzzy Inference System and... AbstractThe context analysis of customer requests in a natural language call routing problem is investigated in the paper. One of the most significant problems in natural language call routing is a comprehension of client request. With the aim of finding a solution to this issue, the Hybrid HMM and ANFIS models become a subject to an examination. Combining different types of models (ANFIS and HMM) can prevent misunderstanding by the system for identification of user intention in dialogue system. Based on these models, the hybrid system may be employed in various language and call routing domains due to nonusage of lexical or syntactic analysis in classification process. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Open Engineering de Gruyter

Context Analysis of Customer Requests using a Hybrid Adaptive Neuro Fuzzy Inference System and Hidden Markov Models in the Natural Language Call Routing Problem

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Publisher
de Gruyter
Copyright
© 2018 Samir Rustamov et al.
ISSN
2391-5439
eISSN
2391-5439
D.O.I.
10.1515/eng-2018-0008
Publisher site
See Article on Publisher Site

Abstract

AbstractThe context analysis of customer requests in a natural language call routing problem is investigated in the paper. One of the most significant problems in natural language call routing is a comprehension of client request. With the aim of finding a solution to this issue, the Hybrid HMM and ANFIS models become a subject to an examination. Combining different types of models (ANFIS and HMM) can prevent misunderstanding by the system for identification of user intention in dialogue system. Based on these models, the hybrid system may be employed in various language and call routing domains due to nonusage of lexical or syntactic analysis in classification process.

Journal

Open Engineeringde Gruyter

Published: Apr 5, 2018

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