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.

5G Performance Testing of Mobile Chatbot Applications

Abstract: A Chatbot is an application that is designed to provide automated contextual communication. Today most chatbots are implemented on top of or as a gateway to popular messaging services, such as Facebook Messenger, Skype and Viber. Chatbots can be classified into many categories regarding their usage, such as conversational commerce, customer support, education, marketing and others. Due to their agile deployment ability on top of virtualized and serverless environments,chatbots are expected to play a pivotal role in the forthcoming 5G networks, which support virtualization capabilities at the edge of the network, making feasible the provision of diversified chatbot services customized to each user needs and requests. However, chatbot QoS might be affected under congested network conditions or in areas with poor signal reception quality. Currently, the performance of the chatbot has not been researched, while the users are experiencing only the results of the potential QoS degradation, such as loss or re-ordering of messages. This paper provides an experimental study of the chatbot apps performance/QoS under different network and reception conditions. The experiment was conducted using the 5G mobile network emulation testbed created and provided by the EU-funded TRIANGLE project.

Machine natural language processing for summarization and sentiment analysis

Abstract: A virtual agent can implement a "chatbot" to provide output based on predictive/prescriptive models for incidents. The virtual agent can integrate with natural language processor for text analysis and summary report generation. The virtual agent can integrate with cognitive search to enable processing of search requests and retrieval of search results. The virtual agent uses computing processes with self-learning systems that use data mining, pattern recognition and natural language processing to mimic the way the human brain works. The virtual agent provides an automated IT system that is capable of resolving incidents without requiring human assistance. The virtual agent can display condensed summaries of a large amount of data and can link the summaries to predictive models and operational risk models to identify risk events and provide summaries of those events.

Career Counselling Chatbot Using Cognitive Science and Artificial Intelligence

Abstract: Career counselling is a process that focuses on helping an individual understand his/her own self, as well as work trends so that they can take an informed decision about career and education. Therefore, career counselling plays a very vital role but there is a lack of importance for career counselling in schools and colleges. Hence, this paper reflects the methods through which personalized career counselling for students can be implemented. To achieve this, a chatbot is used which is a computer program that mimics human conversations using artificial intelligence and cognitive science. Users can start conversations with the bot on a different channel like Facebook Messenger, Skype, Slack and SMS. Initially, the chatbot will start by asking the user for the personal information. Next, the bot will conduct a series of psychometric tests specifically holland test for suggesting career options which are best suited and big 5 test for identifying a user’s overall personality. According to the results, the bot will suggest a list of job opportunities well suited for the user. Once the user has selected a job, the chatbot will start mentoring the user in achieving all the necessary skill set for that particular job. All this user information will be stored in MongoDB. While the user interacts with the user, the chatbot will capture the facial and textual emotions of the user to know the interests of the user. During the training process, the bot will create and maintain a progress report and update this time to time in the user’s E-portfolio. This portfolio will help the user as well as the job providers in recognizing the genuine skill set of the user. Usually, the mentoring process is affected by the language barrier and can result in extreme misunderstanding, and our chatbot is capable enough to interact with the user in their preferred language and will be available 24 × 7 (Brown, Career information, career counselling, & career development (2006) [1]).

Balinese Historian Chatbot using Full-Text Search and Artificial Intelligence Markup Language Method

Abstract: In the era of technology, various information could be obtained quickly and easily. The history of Bali is one of the information that could be obtained. Balinese have known their history through Babad and stories which are told through generations. Babad is traditionalhistorical writing which tells important event that has happened. As technology evolves, Balinese‘s interest in studying their own history has been decreased. It is caused by people interest in studying history books and chronicles tend to decrease over time. Therefore, an innovation of technology, which able to convert historical data from printed media to digital media, is needed. The technology that could be used is Chatbot technology; a computer program that could carry out conversations. Chatbot technology is used to make people learning history easily by using Instant Messenger LINE as a platform to communicate. This Chatbot uses two methods, namely the Artificial Intelligence Markup Language method and the Full-Text Search method. The Artificial Intelligence Markup Language method is used as the process of making characteristic of questions and answers. The Full-Text Search method is the process of matching answers based on user input. This chatbot only uses Indonesian to communicate. The results of this study are a Chatbot that could be accessed by using Instant Messenger LINE and could communicate like historian expert.

Artificial Intelligence–Based Chatbots for Promoting Health Behavioral Changes: Systematic Review

Abstract: Background Artificial intelligence (AI)–based chatbots can offer personalized, engaging, and on-demand health promotion interventions. Objective The aim of this systematic review was to evaluate the feasibility, efficacy, and intervention characteristics of AI chatbots for promoting health behavior change. Methods A comprehensive search was conducted in 7 bibliographic databases (PubMed, IEEE Xplore, ACM Digital Library, PsycINFO, Web of Science, Embase, and JMIR publications) for empirical articles published from 1980 to 2022 that evaluated the feasibility or efficacy of AI chatbots for behavior change. The screening, extraction, and analysis of the identified articles were performed by following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Results Of the 15 included studies, several demonstrated the high efficacy of AI chatbots in promoting healthy lifestyles (n=6, 40%), smoking cessation (n=4, 27%), treatment or medication adherence (n=2, 13%), and reduction in substance misuse (n=1, 7%). However, there were mixed results regarding feasibility, acceptability, and usability. Selected behavior change theories and expert consultation were used to develop the behavior change strategies of AI chatbots, including goal setting, monitoring, real-time reinforcement or feedback, and on-demand support. Real-time user-chatbot interaction data, such as user preferences and behavioral performance, were collected on the chatbot platform to identify ways of providing personalized services. The AI chatbots demonstrated potential for scalability by deployment through accessible devices and platforms (eg, smartphones and Facebook Messenger). The participants also reported that AI chatbots offered a nonjudgmental space for communicating sensitive information. However, the reported results need to be interpreted with caution because of the moderate to high risk of internal validity, insufficient description of AI techniques, and limitation for generalizability. Conclusions AI chatbots have demonstrated the efficacy of health behavior change interventions among large and diverse populations; however, future studies need to adopt robust randomized control trials to establish definitive conclusions.