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.

Developing FB Chatbot Based on Deep Learning Using RASA Framework for University Enquiries

Abstract: Smart systems for Universities powered by Artificial Intelligence have been massively developed to help humans in various tasks. The chatbot concept is not something new in today society which is developing with recent technology. College students or candidates of college students often need actual information like asking for something to customer service, especially during this pandemic, when it is difficult to have an immediate face-to-face meeting. Chatbots are functionally helping in several things such as curriculum information, admission for new students, schedule info for any lecture courses, students grade information, and some adding features for Muslim worships schedule, also weather forecast information. This Chatbot is developed by Deep Learning models, which was adopted by an artificial intelligence model that replicates human intelligence with some specific training schemes. This kind of Deep Learning is based on RNN which has some specific memory savings scheme for the Deep Learning Model, specifically this chatbot using LSTM which already integrates by RASA framework. LSTM is also known as Long Short Term Memory which efficiently saves some required memory but will remove some memory that is not needed. This Chatbot uses the FB platform because of the FB users have already reached up to 60.8% of its entire population in Indonesia. Here's the chatbot only focuses on case studies at campus of the Magister Informatics FTI University of Islamic Indonesia. This research is a first stage development within fairly sufficient simulate data.

Model-Driven Chatbot Development

Abstract: Chatbots are software services accessed via conversation in natural language. They are increasingly used to help in all kinds of procedures like booking flights, querying visa information or assigning tasks to developers. They can be embedded in webs and social networks, and be used from mobile devices without installing dedicated apps. While many frameworks and platforms have emerged for their development, identifying the most appropriate one for building a particular chatbot requires a high investment of time. Moreover, some of them are closed – resulting in customer lock-in – or require deep technical knowledge.

Designing Intelligent Personalized Chatbot for Hotel Services

Abstract: Development of chatbot in customer services and sales are remarkable. However, there is only little research in developing chatbot-hotel in Indonesia. Chatbot has many advantages for both hotel and mobile users to improve convenience, reduce service, sales and support costs, one-to-one marketing and new data collections. Using chatbot, customers using smartphone can reach a hotel anytime and anywhere with personalized services related to their needs. The customers can find out availability of rooms, price, booking and have a personal front office that provide the real-time and context-relevant information about hotel services. Therefore, we develop an interactive intelligent personalized chatbot-hotel by using AIML and Google Flutter. Flutter is used as it is easy to develop the chatbot-hotel in the cross-platform mobile application. The outcome of this work is a prototype chatbot-hotel on mobile platform especially for Indonesian users. This chatbot includes all services in the hotels and able to give the personalized services to the customers before arrive in the hotel. It can accommodate the customer needs and to up-selling the hotel facilities.

Intelligent tutoring chatbot for solving mathematical problems in High-school

Abstract: Nowadays, information technology is applied for teaching and learning in high-school. It is an essential trend for the modern education, especially building intelligent systems to support the learning of mathematics. In the math subjects of Vietnamese high-school, problems about surveying properties of a function are popular in high-school exams. There are some current tools can solve them automatically. However, they only can display the graph of a function; they cannot solve problems about determining the value of a parameter to satisfy some conditions about this function’s properties. In this paper, we will present a method to design an intelligent chatbot for solving problems in this knowledge domain. It plays as an instructor to give some tips and tutor the learner how to solve problems automatically. This program can communicate with the learner through the question-answering process by chatbot. This tutoring of our system simulates the tutoring method of the teacher to the students in practice.

Uncanny Valley Effects on Chatbot Trust, Purchase Intention, and Adoption Intention in the Context of E-Commerce: The Moderating Role of Avatar Familiarity

Abstract: This study investigates the effect of chatbot humanization on the perception of eeriness, trust, and users’ behavioral intention. Specifically, this study employed a 2 (humanization of chatbot agent avatar: hyperrealistic-animated vs. cartoonish-still) × 2 (avatar familiarity: celebrity avatar vs. non-celebrity avatar) between-subjects experiment (N = 185), in which participants were asked to purchase a laptop from an e-commerce vendor by interacting with a chatbot agent. Based on predictions from the uncanny valley effect hypothesis (UVE), enhancing the human likeness of a chatbot agent through visual realism and animacy was predicted to negatively influence users’ trust in the chatbot agent and behavioral intention as a consequence of the activation of a negative affective state (i.e., a feeling of eeriness). Consistent with our predictions, the results from PLS-SEM showed that (a) enhancing the human likeness of a chatbot agent significantly increased users’ feeling of eeriness, (b) the feeling of eeriness negatively influenced users’ trust in the chatbot agent, c) trust, determined by the feeling of eeriness, significantly affected users’ purchase intention and willingness to reuse the chatbot, and d) the relationship between humanization and eeriness significantly moderated by the familiarity of the chatbot avatar. We discuss the theoretical implications of the current study on UVE as well as its practical implications for the implementation of anthropomorphized chatbot agents in the e-commerce context.