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Building an Enterprise Chatbot = Wor...
~
Shivam, Shrey.
Building an Enterprise Chatbot = Work with Protected Enterprise Data Using Open Source Frameworks /
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Building an Enterprise Chatbot/ by Abhishek Singh, Karthik Ramasubramanian, Shrey Shivam.
其他題名:
Work with Protected Enterprise Data Using Open Source Frameworks /
作者:
Singh, Abhishek.
其他作者:
Ramasubramanian, Karthik.
面頁冊數:
XXII, 385 p. 102 illus.online resource. :
Contained By:
Springer Nature eBook
標題:
Application software. -
電子資源:
https://doi.org/10.1007/978-1-4842-5034-1
ISBN:
9781484250341
Building an Enterprise Chatbot = Work with Protected Enterprise Data Using Open Source Frameworks /
Singh, Abhishek.
Building an Enterprise Chatbot
Work with Protected Enterprise Data Using Open Source Frameworks /[electronic resource] :by Abhishek Singh, Karthik Ramasubramanian, Shrey Shivam. - 1st ed. 2019. - XXII, 385 p. 102 illus.online resource.
Chapter 1: Processes in the Banking and Insurance Industry -- Chapter 2: Identifying the Sources of Data -- Chapter 3: Mining Intents from the Data Sources -- Chapter 4: Building a Business Use-Case -- Chapter 5: Natural Language Processing (NLP) -- Chapter 6: Building Chatbots Using Popular Platforms -- Chapter 7: Chatbot Platforms -- Chapter 8: Chatbot Integration Mechanism -- Chapter 9: Deployment and Continuous Improvement Framework.
Explore the adoption of chatbots in business by focusing on the design, deployment, and continuous improvement of chatbots in a business, with a single use-case from the banking and insurance sector. This book starts by identifying the business processes in the banking and insurance industry. This involves data collection from sources such as conversations from customer service centers, online chats, emails, and other NLP sources. You’ll then design the solution architecture of the chatbot. Once the architecture is framed, the author goes on to explain natural language understanding (NLU), natural language processing (NLP), and natural language generation (NLG) with examples. In the next section, you’ll discuss the importance of data transfers using natural language platforms, such as Dialogflow and LUIS, and see why this is a key process for chatbot development. In the final section, you’ll work with the RASA and Botpress frameworks. By the end of Building an Enterprise Chatbot with Python, you will be able to design and develop an enterprise-ready conversational chatbot using an open source development platform to serve the end user. You will: Identify business processes Design the solution architecture for a chatbot Integrate chatbots with internal data sources using APIs Discover the differences between natural language understanding (NLU), natural language processing (NLP), and natural language generation (NLG) Work with deployment and continuous improvement through representational learning.
ISBN: 9781484250341
Standard No.: 10.1007/978-1-4842-5034-1doiSubjects--Topical Terms:
528147
Application software.
LC Class. No.: QA76.76.A65
Dewey Class. No.: 004
Building an Enterprise Chatbot = Work with Protected Enterprise Data Using Open Source Frameworks /
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Chapter 1: Processes in the Banking and Insurance Industry -- Chapter 2: Identifying the Sources of Data -- Chapter 3: Mining Intents from the Data Sources -- Chapter 4: Building a Business Use-Case -- Chapter 5: Natural Language Processing (NLP) -- Chapter 6: Building Chatbots Using Popular Platforms -- Chapter 7: Chatbot Platforms -- Chapter 8: Chatbot Integration Mechanism -- Chapter 9: Deployment and Continuous Improvement Framework.
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