Topic
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.
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01 Dec 2019
TL;DR: The evolution of chatbots is traced and the key insights that were obtained pertaining to the crucial factors that influence chatbot design, generation, and development are elaborated on.
Abstract: Conversation Agents also known as Chatbots are considered the next big thing in the modern technological era. Chatbots aim to emulate humans, by mimicking human conversation in the most realistic way possible. There are several methods to generate such intelligent agents. Thus to evaluate the effectiveness of the various approaches, a systematic review of the approaches is required. This paper traces the evolution of chatbots and also elaborates on the impact chatbots have in different industries. Additionally, it also presents a survey of the different modern chatbot methodologies that different researchers have proposed. When analyzing the different approached, this paper has taken into consideration the dataset, input-output, design, development, performance metric, and limitations into consideration. In the end, we've elaborated on the key insights that were obtained pertaining to the crucial factors that influence chatbot design, generation, and development.
14 citations
TL;DR: A framework and functionality of a chatbot developed using web technologies that can be a better solution for data extraction from local hospital which functioning as a good communication channel for both users and hospital staff and helpful in reducing the crowd is presented.
14 citations
TL;DR: An authoring tool is presented together with a new scheme to control the communication process better than current chatbot technologies and approaches allow and show future prospects offered by storytelling mechanisms.
Abstract: “CitizenTalk”, an applied research project at FH Erfurt, investigates the potential and challenges of interactive communication using chatbots as an innovative tool for involving citizens in public planning processes. This comprises research into the state of the art in virtual planning communication, as well as the technical possibilities of chatbot communication. We present the opportunities and limitations associated with the adoption of chatbot concepts and show future prospects offered by storytelling mechanisms. An authoring tool is presented together with a new scheme to control the communication process better than current chatbot technologies and approaches allow.
14 citations
03 Apr 2019
TL;DR: A semi-supervised artificially intelligent chatbot framework that can automate parts of primary interaction and customer service and can generate contextualized responses in any language without depending much on rich NLP background and a vast number of a prior data set is proposed.
Abstract: In today’s business world, providing reliable customer service is equally important as delivering better products for maintaining a sustainable business model. As providing customer service require...
14 citations
01 Nov 2018
TL;DR: A neural-based conversational solution that employs BiLSTM with attention mechanism and can help customer service agents provide a high-quality customer experience by reducing customer wait time and by applying the knowledge accumulated from customer interactions in future applications is developed.
Abstract: Hiring seasonal workers in call centers to provide customer service is a common practice in B2C companies. The quality of service delivered by both contracting and employee customer service agents depends heavily on the domain knowledge available to them. When observing the internal group messaging channels used by agents, we found that similar questions are often asked repetitively by different agents, especially from less experienced ones. The goal of our work is to leverage the promising advances in conversational AI to provide a chatbot-like mechanism for assisting agents in promptly resolving a customer's issue. In this paper, we develop a neural-based conversational solution that employs BiLSTM with attention mechanism and demonstrate how our system boosts the effectiveness of customer support agents. In addition, we discuss the design principles and the necessary considerations for our system. We then demonstrate how our system, named "Isa" (Intuit Smart Agent), can help customer service agents provide a high-quality customer experience by reducing customer wait time and by applying the knowledge accumulated from customer interactions in future applications.
14 citations