Chatbot

About: Chatbot is a research topic. Over the lifetime, 2415 publications have been published within this topic receiving 24372 citations. The topic is also known as: IM bot & AI chatbot.

Chatbot Components and Architectures

Abstract: In the Introduction, we discussed that chatbot platforms offered by enterprises turned out to be good for simple cases, not really enterprise-level deployments In this chapter we make a first step towards industrial–strength chatbots We will outline the main components of chatbots and show various kinds of architectures employing these components The descriptions of these components will be the reader’s starting points to learning them in-depth in the consecutive chapters

Towards developing a pocket therapist: An intelligent adaptive psychological support chatbot against mental health disorders in a pandemic situation

Abstract: Nowadays with COVID-19 ongoing epidemic outbreak, containment for weeks was one of the most effective measures adopted to deal with the spread of the virus until a vaccine could be efficient. Over that period, increased anxiety, depression, suicide attempts and post-traumatic stress disorder are accumulated. Several studies referred to the need of using chatbots, which recognizes human emotions in such pandemic contexts. More recently, numerous research papers improved the ability of artificial intelligence methods to recognize human emotion. However, they are still limited. The aim of this paper is the development of a chatbot against the disturbing psychic consequences of the pandemic, taking human emotion recognition into account. The object is to help people; especially students; suffering from mental disorders, by progressively understanding the reasonsbehind them. This innovative chatbot was developed by using the natural language processing model of deep learning. An advanced model of deep learning has been elaborated the intention for people and that to help them to regulate their mood and to reduce distortion of negative thoughts, that why a collection of a new database was done. The sequence-to-sequence model encoder and decoder consist of Long short-term memory cells and it is defined with the bi-directional dynamic recurrent neural network packets.

Chatbot Evaluation as Knowledge Application: a Case Study of PT ABC

Abstract: ELISA chatbot acts as an automated answering machine to users' problem in PT ABC. Implemented in May 2018, it succeeded to provide a faster response time than offline customer service. However, it still has issues in delivering accurate and appropriate responses. One of the reasons is the lack of system control and evaluation. This paper aims to evaluate how ELISA chatbot, as a knowledge application, benefits the company using DeLone & McLean model of information system as a reference. A survey was conducted, and SEM-PLS was utilized to process the data. The result shows that information quality, service quality, and intention to use significantly affect user satisfaction in ELISA. Suggestions for ELISA improvement includes machine learning technology utilization and nonfunctional improvements.

FLOSS FAQ chatbot project reuse: how to allow nonexperts to develop a chatbot

Abstract: FAQ chatbots possess the capability to provide answers to frequently asked questions of a particular service, platform, or system. Currently, FAQ chatbot is the most popular domain of use of dialog assistants. However, developing a chatbot project requires a full-stack team formed by numerous specialists, such as dialog designer, data scientist, software engineer, DevOps, business strategist and experts from the domain, which can be both time and resources consuming. Language processing can be particularly challenging in languages other than English due to the scarcity of training datasets.Most of the requirements of FAQ chatbots are similar, domain-specific, and projects could profit from Open Source Software (OSS) reuse. In this paper, we examine how OSS FAQ chatbot projects can benefit from reuse at the project level (black-box reuse). We present an experience report of a FLOSS FAQ chatbot project developed in Portuguese to an e-government service in Brazil. It comprises of the chatbot distribution service, as well as for analytics tool integrated and deployed on-premises. We identified assets that could be reused as a black-box and the assets that should be customized for a particular application. We categorized these assets in architecture, corpus, dialog flows, machine learning models, and documentation. This paper discusses how automation, pre-configuration, and templates can aid newcomers to develop chatbots in Portuguese without the need for specialized skills required from tools in chatbot architecture. Our main contribution is to highlight the issues non-English FAQ chatbots projects will likely face and the assets that can be reused. It allows non-chatbot experts to develop a quality-assured OSS FAQ chatbot in a shorter project cycle.

Ai Chatbots: Transforming the Digital World

Abstract: There is no doubt that Artificial Intelligence is changing the world and the outlook of technology and is no longer considered as the future technology as we have already started experiencing it in our daily lives. Artificial Intelligence has been adopted continuously at a rapid scale by organizations and business for the automation of their process. Artificial intelligence has laid the foundation of the creation of intelligent agents that we today known as chat bots. Chat bots have brought a revolution in the business communication process as well as helped in attaining customer satisfaction at a large scale. This chapter describes about the history of chat bots along with their development platforms. For the better understanding we have created conversations with various available chat bot platforms and also tried to present the procedure of a Chatbot creation.