Context Analysis of Customer Requests using a Hybrid Adaptive Neuro Fuzzy Inference System and Hidden Markov Models in the Natural Language Call Routing Problem
| Autor: | Elshan Mustafayev, Mark A. Clements, Samir Rustamov |
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| Rok vydání: | 2018 |
| Předmět: |
0209 industrial biotechnology
Environmental Engineering Computer science Aerospace Engineering text mining 02 engineering and technology natural language call routing 020901 industrial engineering & automation 0202 electrical engineering electronic engineering information engineering General Materials Science Electrical and Electronic Engineering Hidden Markov model Civil and Structural Engineering Adaptive neuro fuzzy inference system anfis business.industry Mechanical Engineering learning user intention Engineering (General). Civil engineering (General) Context analysis Call routing 020201 artificial intelligence & image processing hmm Artificial intelligence TA1-2040 business Natural language |
| Zdroj: | Open Engineering, Vol 8, Iss 1, Pp 61-68 (2018) |
| ISSN: | 2391-5439 |
| DOI: | 10.1515/eng-2018-0008 |
| Popis: | 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 nonusage of lexical or syntactic analysis in classification process. |
| Databáze: | OpenAIRE |
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