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Proceedings ArticleDOI

Desirable Features of a Chatbot-building Platform

TL;DR: 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.
Citations
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Proceedings ArticleDOI
15 May 2022
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.
Abstract: In this research, we constructed a topic selection system in order to provide “topics that users are interested in and are not familiar with” from the dialogue system side. To achieve this goal, we used a concept distance to provide topics that the user is not familiar with, and improved the accuracy by removing those with a short conceptual distance. Many words in the conversation are not included in the thesaurus dictionary. We constructed a conceptual distance measurement model using machine learning so that the conceptual distance can be measured even for words that are not included in the thesaurus dictionary. As a result of the subject experiment, it was confirmed that the proposal system can be used to provide topics that the user is interested in and is not familiar with.

2 citations

Proceedings ArticleDOI
08 Sep 2022
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.
Abstract: The Covid-19 pandemic has brought many changes in the healthcare industry lately. As things are going normal with time, many health projects designed and used during emergencies are left unexploited. To make the perpetual use of those technologies, the current need should be taken into consideration along with necessary ideas and frameworks to evolve the existing system into. To demonstrate the same, in this paper, we have presented 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 chatbot system. This proposed system showcases how a similar Covid-19 system can be developed into a sophisticated healthcare service. This paper emphasises adding Artificial Intelligence to any conventional software via chatbot services which would broaden the services it provides even further. In order to find out the probable best technology to integrate AI with, about 50 papers have been analysed and out of which 27 relevant papers have been included in the literature review. In future, we intend to add medical support and other intelligence-based services to our system in order to meet user requirements and essential features in the field of healthcare.

2 citations

Proceedings ArticleDOI
08 Sep 2022
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.
Abstract: The Covid-19 pandemic has brought many changes in the healthcare industry lately. As things are going normal with time, many health projects designed and used during emergencies are left unexploited. To make the perpetual use of those technologies, the current need should be taken into consideration along with necessary ideas and frameworks to evolve the existing system into. To demonstrate the same, in this paper, we have presented 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 chatbot system. This proposed system showcases how a similar Covid-19 system can be developed into a sophisticated healthcare service. This paper emphasises adding Artificial Intelligence to any conventional software via chatbot services which would broaden the services it provides even further. In order to find out the probable best technology to integrate AI with, about 50 papers have been analysed and out of which 27 relevant papers have been included in the literature review. In future, we intend to add medical support and other intelligence-based services to our system in order to meet user requirements and essential features in the field of healthcare.

1 citations

Book ChapterDOI
01 Jan 2022
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.
Abstract: AbstractStroke is a second leading cause of death globally according to WHO Global Health Estimates and is listed in top 5 causes of disability globally from past few decades. Especially in developing country like India having population over 1 Billion, stroke rate is much higher than any other developing countries, and in this current pandemic situation the incident of stroke has doubled in past few years. So awareness about general population on stroke risk factors and symptoms is necessary for prevention against stroke and immediate effective treatment. The aim of this project is to assist general population of risk factor, warning symptoms of stroke, prevention and immediate effective treatment of stroke as soon as possible. To achieve this Chatbot is design 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. The main goal of this research is to look at how few popular Machine Learning algorithms function and to forecast stroke with high accuracy.KeywordsStrokeChatBotDemographic dataMachine LearningRandom Forest ClassifierDecision Tree ClassifierSupport Vector ClassifierDeep LearningNeural Network
Proceedings ArticleDOI
01 Dec 2022
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.
Abstract: In this paper, we present a Natural Language Processing (NLP)-empowered virtual course assistant solution that supports online teaching and learning in the context of the COVID-19 pandemic. We leverage advanced technologies of pre-trained language models in NLP to construct several fundamental functionalities for the virtual course assistant. The assistant is designed to answer general course enquiries to reduce time-consuming and repeated human responses, to answer course-related knowledge questions by understanding both queries and teaching materials, and to analyze students' feedback via sentiment analysis. Additionally, we have constructed the course-related database and cross-platform virtual assistants for both website and mobile applications. Different pre-trained models are utilized to fine-tune the dataset in each type of model. By comparing different datasets and analyzing their performance, the best performance model is selected for the virtual assistant. Empirically, adopting NLP-empowered virtual course assistants in class improves teaching and learning experiences: With the help of an NLP-empowered virtual course assistant, the teaching team could devote more effort and time to answering complex questions; For students, an immediate response increases their motivation to study. Thus, the online system could give an excellent user experience to a wide variety of users. Our code and dataset are released at https://github.com/Heriannan/NLP-for-educationVirtualAssistant.
References
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Proceedings ArticleDOI
14 Feb 2020
TL;DR: This work presents the concept of Intent Sets - an Architectural choice, that impacts the overall accuracy of the chatbot and shows that the same chatbot can be built choosing one out of many possible Intent Sets.
Abstract: "Chatbot" is a colloquial term used to refer to software components that possess the ability to interact with the end-user using natural language phrases. Many commercial platforms are offering sophisticated dashboards to build these chatbots with no or minimal coding. However, the job of composing the chatbot from real-world scenarios is not a trivial activity and requires a significant understanding of the problem as well as the domain. In this work, we present the concept of Intent Sets - an Architectural choice, that impacts the overall accuracy of the chatbot. We show that the same chatbot can be built choosing one out of many possible Intent Sets. We also present our observations collected through a set of experiments while building the same chatbot over three commercial platforms - Google Dialogflow, IBM Watson Assistant and Amazon Lex.

4 citations