Building an Enterprise Chatbot: Work with Protected Enterprise Data Using Open Source Frameworks (Paperback)

Chapter 1: Processes in the Banking and Insurance Industry

The chapter will focus on explaining some core process within the banking and insurance industry that is suitable for a chatbot application.

No of pages: 30

Chapter 2: Identifying the Sources of Data

This chapter will discuss sources of data for conversation and action-based event triggers for a chatbot. Conversation courses would be from customer service centers, online chats, emails and other NLP sources, while action sources are customer account details and more personalize data.

No of pages: 30

Chapter 3: Mining Intents from the Data Sources

This chapter will discuss how to build a business-specific intent engine for chatbots.

No of pages: 30

Chapter 4: Building a Business Use-Case

This chapter will focus on how to identify the right business process to introduce chatbots. It will also discuss how to look at some of the metrics of success and RoI given a chatbot is deployed.

No of pages: 30

Chapter 5: Natural Language Processing (NLP)

Chapter Goal: This chapter focusses on processing and understanding natural language through the computer algorithm. It also introduces how to prepare data for applying the NLP algorithms. We will use Stanford CoreNLP, NLTK, gensim, OpenIE tools to explore and model.

No of pages: 80

Sub - topics

Introduction: Question & answering, information extraction, sentiment analysis, Machine translation,

Text processing: Regex, tokenization, normalization ? lower case, lemmatization, stemming (Porters Algorithm), sentence segmentation

Converting text to features: Syntactical parsing ? dependency grammar, PoS, entity parsing ? phrase detection, topic modeling, statistical features ? TF-IDF, word embeddings

Classification ? spam filter using naive Bayes, sentiment analysis using SVM on Lexicon and text feature.

NLP Tools ? nltk, genism, openIE, CoreNLP

Chapter 6: Building Chatbots Using Popular Platforms

For general purpose chatbots, publicly available cloud services can be used to deploy chatbots faster and without any DevOps overhead. We shall discuss some of the major chatbot development platforms available in the market.

No of pages: 50

Sub-Topics

Microsoft Bot framework with LUIS

Google’s DialogFlow

Amazon Lex with Lambda

Bottr, Chatfuel and others

Open framework RASA and Botpress

Chapter 7: Deployment and Continuous Improvement Framework

In this chapter we shall discuss and implement a custom built chatbot . We will discuss designing and implementing state machines and their different state transitions, and how they are critical to maintain the context of user utterance as well as in defining the chat flow using sessions that contains long term and short-term attributes.

No of pages: 50

Sub-topics:

Public endpoint creation

Intent engine development and deployment as API

Building state machine

Integration with Facebook messenger

Deployment of chatbot on AWS

Logging

Mining conversation log to improve intent engine

Recommending similar/next questions, pushing information based on needs prediction

Abhishek Singh (지은이)    정보 더보기

Karthik Ramasubramanian (지은이)    정보 더보기

Shrey Shivam (지은이)    정보 더보기

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