Chatbots: History, technology, and applications
By Eleni Adamopoulou, Lefteris Moussiades. 2020
929 citations recorded by the source corpus.
Abstract This literature review presents the History, Technology, and Applications of Natural Dialog Systems or simply chatbots. It aims to organize critical information that is a necessary background for further research activity in the field of chatbots. More specifically, while giving the historical evolution, from the generative idea to the present day, we point out possible weaknesses of each stage. After we present a complete categorization system, we analyze the two essential implementation technologies, namely, the pattern matching approach and machine learning. Moreover, we compose a general architectural design that gathers critical details, and we highlight crucial issues to take into account before system design. Furthermore, we present chatbots applications and industrial use cases while we point out the risks of using chatbots and suggest ways to mitigate them. Finally, we conclude by stating our view regarding the direction of technology so that chatbots will become really smart.
Subfields: Artificial Intelligence, Social Psychology
View Paper: https://www.semanticscholar.org/paper/5154ee5b479e6b27474bf6d2803b7655672a03e5
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
In Social Psychology
Citations in the corpus
- Will ChatGPT get you caught? Rethinking of Plagiarism Detection (2023, background): “Although the first chatbot, called Eliza, dates back to 1966 [20], the modern chatbot systems have emerged since around 2016 with a rapid increase in popularity till today [1].”
- The rise and potential of large language model based agents: a survey (2025, positive): “With the rapid development of AI, conversational agents have garnered extensive attention in various forms [377] and in various scenarios [378–380].”
- “Chatting with ChatGPT”: Analyzing the factors influencing users' intention to Use the Open AI's ChatGPT using the UTAUT model (2023, background): “Over the next few decades, researchers created increasingly sophisticated chatbots, such as Parry, which simulated a patient with paranoid schizophrenia [48], and Jabberwacky, which used machine learning to generate responses based on previous conversations [32,49].”
- New Era of Artificial Intelligence in Education: Towards a Sustainable Multifaceted Revolution (2023, background): “The development of modern chatbots began in 2016 and has accelerated up to the current date [2].”
- ChatGPT and a new academic reality: Artificial Intelligence‐written research papers and the ethics of the large language models in scholarly publishing (2023, methodology): “Chatbots, which are computer programs designed to mimic human conversation, are one example of the practical uses of these technologies (Adamopoulou & Moussiades, 2020a).”
- The Programmer’s Assistant: Conversational Interaction with a Large Language Model for Software Development (2023, background): “Using natural language to interact with technology has had a long research history [2], starting in the 1960s with pattern-matching approaches like Eliza [104], and continuing to today with state-of-the-art large language modelbased conversational systems [107] such as Meena [3] and BlenderBot [84].”
- Artificially intelligent chatbots in digital mental health interventions: a review (2021, background): “the chatbot feel less human-like [61] and reduces users’ motivation to continue the program [110].”
- The Political Biases of ChatGPT (2023, background): “…architecture (Vaswani et al. 2017) have pushed the state-of-the-art substantially in natural language tasks such as machine translation (Dabre et al. 2020), sentiment analysis (Ain et al. 2017), name entity recognition (Li et al. 2022), or dialogue bots (Adamopoulou and Moussiades 2020).”