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

dc.contributor.author	Rustamov, Samir
dc.contributor.author	Mustafayev, Elshan
dc.contributor.author	Clements, Mark A.
dc.date.accessioned	2022-05-12T06:51:00Z
dc.date.available	2022-05-12T06:51:00Z
dc.date.issued	2018
dc.identifier.uri	http://hdl.handle.net/20.500.12181/371
dc.description.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.	en_US
dc.language.iso	en	en_US
dc.publisher	De Gruyter	en_US
dc.rights	Attribution-NonCommercial-NoDerivs 3.0 United States	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/us/	*
dc.subject.lcsh	Natural Language Call Routing.	en
dc.subject.lcsh	Text Mining.	en
dc.subject.lcsh	ANFIS.	en
dc.subject.lcsh	HMM.	en
dc.title	Context Analysis of Customer Requests using a Hybrid Adaptive Neuro Fuzzy Inference System and Hidden Markov Models in the Natural Language Call Routing Problem	en_US
dc.type	Article	en_US