Inquiry chatbot with cloud computing
The project aims to provide an efficient solution to replace the traditional call center model which is widely used in the industries. Traditional call centers are labor intensive and are unable to handle variable throughput efficiently. This is due to its fixed bandwidth to handle incoming calls. T...
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2018
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sg-ntu-dr.10356-754092023-07-07T17:38:38Z Inquiry chatbot with cloud computing Sathish Jayabalan Gan Woon Seng School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering The project aims to provide an efficient solution to replace the traditional call center model which is widely used in the industries. Traditional call centers are labor intensive and are unable to handle variable throughput efficiently. This is due to its fixed bandwidth to handle incoming calls. The proposed solution will have the call center infrastructure built using Amazon Web Services. The cloud services provider enables the development of the various components of a call center. Amazon Lex service will provide the Natural Language Understanding and Automatic Speech Recognition which allows developer to build lifelike conversational bots which provides highly engaging user interactions. The project will be implemented in 2 phases. First phase consists of the building conversational chatbot on Alexa-enabled devices using Alexa Custom Skills Kit. Second phase includes the integration of the Amazon Connect (cloud-based contact center) directly to the Lex Bot. Interactions with AWS NoSQL Database Service (DynamoDB) and Simple Notification Service (SNS) will be implemented in both phases. From the project, the factors affecting the accuracy of the chatbot, to match user’s utterance to their intent, were established. These factors mainly depend on the quantity and diversity of the enumeration values provided by the developer for the sample utterances. Bachelor of Engineering 2018-05-31T03:58:16Z 2018-05-31T03:58:16Z 2018 Final Year Project (FYP) http://hdl.handle.net/10356/75409 en Nanyang Technological University 51 p. application/pdf |
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DRNTU::Engineering::Electrical and electronic engineering Sathish Jayabalan Inquiry chatbot with cloud computing |
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The project aims to provide an efficient solution to replace the traditional call center model which is widely used in the industries. Traditional call centers are labor intensive and are unable to handle variable throughput efficiently. This is due to its fixed bandwidth to handle incoming calls. The proposed solution will have the call center infrastructure built using Amazon Web Services. The cloud services provider enables the development of the various components of a call center. Amazon Lex service will provide the Natural Language Understanding and Automatic Speech Recognition which allows developer to build lifelike conversational bots which provides highly engaging user interactions. The project will be implemented in 2 phases. First phase consists of the building conversational chatbot on Alexa-enabled devices using Alexa Custom Skills Kit. Second phase includes the integration of the Amazon Connect (cloud-based contact center) directly to the Lex Bot. Interactions with AWS NoSQL Database Service (DynamoDB) and Simple Notification Service (SNS) will be implemented in both phases. From the project, the factors affecting the accuracy of the chatbot, to match user’s utterance to their intent, were established. These factors mainly depend on the quantity and diversity of the enumeration values provided by the developer for the sample utterances. |
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Gan Woon Seng |
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Gan Woon Seng Sathish Jayabalan |
format |
Final Year Project |
author |
Sathish Jayabalan |
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Sathish Jayabalan |
title |
Inquiry chatbot with cloud computing |
title_short |
Inquiry chatbot with cloud computing |
title_full |
Inquiry chatbot with cloud computing |
title_fullStr |
Inquiry chatbot with cloud computing |
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Inquiry chatbot with cloud computing |
title_sort |
inquiry chatbot with cloud computing |
publishDate |
2018 |
url |
http://hdl.handle.net/10356/75409 |
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1772827782180503552 |