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Proceedings ArticleDOI

Desirable Features of a Chatbot-building Platform

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TLDR
Based on the experiences with three popular chatbot-building platforms - Google Dialogflow, IBM Watson Assistant and Amazon Lex, a list of desirable features that these platforms should exhibit in order to cater to their mixed user base is presented.
Abstract
There is a visible eagerness in the business community to integrate chatbots with their websites and mobile apps. They provide a humanised interface to information and can serve as digital assistants that can perform tasks on behalf of an individual. There are many commercial platforms which provide interfaces to build these chatbots. They are used by both professional software developers as well as people from non-IT backgrounds. Based on our experiences with three popular chatbot-building platforms - Google Dialogflow, IBM Watson Assistant and Amazon Lex, we present a list of desirable features that these platforms should exhibit in order to cater to their mixed user base. We also rate the availability and ease of use of these features on the current versions of these platforms.

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Citations
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Proceedings ArticleDOI

On selection of topics that users are interested in but are not familiar with

TL;DR: The authors constructed a topic selection system to provide topics that users are interested in and are not familiar with from the dialogue system side, and improved the accuracy by removing those with a short conceptual distance.
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An Interactive AI-Powered Web Healthcare System

TL;DR: In this paper , a package of healthcare services powered by Artificial Intelligence via a chatbot system, where a user can entertain the services either by an interactive Graphical User Interface or a conversational chat bot system.
Proceedings ArticleDOI

An Interactive AI-Powered Web Healthcare System

TL;DR: In this paper , a package of healthcare services powered by Artificial Intelligence via a chatbot system, where a user can entertain the services either by an interactive Graphical User Interface or a conversational chat bot system.
Book ChapterDOI

Stroke Awareness ChatBot Assistant with Stroke Risk Prediction Using Demographic Data

TL;DR: In this paper , a Chatbot is designed using Deep Learning for the purpose of awareness, diagnostic evaluation, stroke prediction from user input data and assisting immediate measures if stroke risk prediction is positive.
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An NLP-Empowered Virtual Course Assistant for Online Teaching and Learning

TL;DR: In this paper , a Natural Language Processing (NLP) assisted virtual course assistant solution was proposed to support online teaching and learning in the context of the COVID-19 pandemic.
References
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Book

Developing Enterprise Chatbots: Learning Linguistic Structures

TL;DR: This chapter is an Introduction to the book and analyzes a lack of intelligence as a major bottleneck of current dialogue systems, and briefly survey current trends.
Journal ArticleDOI

Chatbots for Enterprises: Outlook

TL;DR: A new method for chatbot platform evaluation is proposed and the proposed method for the chatbot selection is demonstrated on two sample businesses – a large bank and a small taxi service.
Proceedings ArticleDOI

Hospitality of chatbot building platforms

TL;DR: This work proposes a methodological framework to evaluate support provided by a chatbot platform towards achieving quality in the application, and presents the use of the framework on a simple use case to highlight the phases of evaluation.
Proceedings ArticleDOI

A Reference Architecture for Applications with Conversational Components

TL;DR: This work presents a Reference Architecture for building conversational components of IBM Watson Assistant and Google DialogFlow, and provides two Concrete Architectures for the same.
Proceedings ArticleDOI

Contextual Reactive Pattern on Chatbot building Platforms

TL;DR: The effects of using a platform to build a chatbot is discussed and the Contextual Reactive pattern used for chatbot definition is discussed, which describes the "reaction" that must take place when the context is observed.