Context Analysis of Customer Requests using a Hybrid Adaptive Neuro Fuzzy Inference System and Hidden Markov Models in the Natural Language Call Routing Problem
Date Issued
2018
Author(s)
Rustamov, Samir
Mustafayev, Elshan
Clements, Mark A.
Abstract
The 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 non-usage of lexical or syntactic analysis in classification process.
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 non-usage of lexical or syntactic analysis in classification process.