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.

Chatbots: History, technology, and applications

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.

Chat with Bots Intelligently: A Critical Review & Analysis

Kemajuan teknologi membuat banyak otomatisasi dalam dunia industri, Salah satunya penerapan Chatbot pada industri pendidikan. Dengan teknologi otomatisasi ini, Memudahkan universitas untuk melayani mahasiswa kapanpun waktunya dan dimanapun tempatnya. Kurangnya literasi mahasiswa terhadap fungsi dan penggunaan web kuliah dalam melaksanakan kuliah online menyebabkan banyaknya pertanyaan yang sama secara berulang kepada pihak universitas yang sebenarnya pertanyaan yang sering ditanyakan sudah ditulis dalam daftar pertanyaan yang sering muncul(Faq), seperti: pengumpulan tugas, lupa password , kuliah online, kuliah video conference dan aplikasi web kuliah di android. Dengan menggunakan Chatbot secara otomatis akan menjawab pertanyaan mahasiswa dilaman web kuliah dengan memberikan informasi dan mengarahkan sesuai dengan jawaban pertanyaan. Dalam penelitian ini akan dikembangkan model Chatbot berbasis teks dengan menggunakan algoritma Artificial neural network (ANN). Dataset yang digunakan untuk melakukan pelatihan Chatbot merupakan data pertanyaan sering timbul (Faq) didalam web kuliah yaitu 25 pertanyaan beserta jawaban yang dibagi kedalam 16 label atau kelas. Pengujian dilakukan dengan menggunakan 110 percakapan yang berbeda dengan dataset tetapi mempunyai maksud yang sama. Dari 110 percakapan Chatbot berhasil menjawab dengan tepat sebanyak 107 percakapan dan jawaban salah sebanyak 3 percakapan. Hasil pengujian menunjukkan hasil yang baik yaitu mempunyai akurasi 97,27 % dan kesalahan 2,72 %. Kata Kunci: Chatbot , Artificial Neural Network, ANN, Berbasis teks.

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Algoritma Artificial Neural Network pada Text-based Chatbot Frequently Asked Question (FAQ) Web Kuliah Universitas Nasional

Today is the era of intelligence in machines. With the advances in Artificial Intelligence, machines have started to impersonate different human traits, a chatbot is the next big thing in the domain of conversational services. A chatbot is a virtual person who is capable to carry out a natural conversation with people. They can include skills that enable them to converse with the humans in audio, visual, or textual formats. Artificial intelligence conversational entities, also called chatbots, conversational agents, or dialogue system, are an excellent example of such machines. Obtaining the right information at the right time and place is the key to effective disaster management. The term "disaster management" encompasses both natural and human-caused disasters. To assist citizens, our project is to create a COVID Assistant to provide the need of up to date information to be available 24 hours. With the growth in the World Wide Web, it is quite intelligible that users are interested in the swift and relatedly correct information for their hunt. A chatbot can be seen as a question-and-answer system in which experts provide knowledge to solicit users. This master thesis is dedicated to discuss COVID Assistant chatbot and explain each component in detail. The design of the proposed chatbot is introduced by its seven components: Ontology, Web Scraping module, DB, State Machine, keyword Extractor, Trained chatbot, and User Interface.

An ontology-based chatbot for crises management: use case coronavirus.

Conventionally, human-controlled and machine-controlled virtual characters are studied separately under different theoretical frameworks based on the ontological nature of the particular virtual character. However, in recent years, the technological advancement has made the boundaries between human and machine agency increasingly blurred. This manuscript proposes a theoretical framework that can explain how various virtual characters, regardless of their ontological agency, can be treated as unique social actors with a focus on perceived authenticity. Specifically, drawing on the authenticity model in computer-mediated communication proposed by Lee (2020) and a typology of virtual characters, a multi-layered perceived authenticity model is proposed to demonstrate how virtual characters do not have to be perceived as humans and yet can be perceived as authentic to their human interactants.

Perceived authenticity of virtual characters makes the difference

In the modern era of technology, chatbot is the next big thing in the domain of conversational services. A chatbot is a virtual person who can effectively talk to any human being using interactive textual as well as verbal skills. There are many statistics available which suggest that integration of chatbot in any business as a part of their customer service increases the business progress and customer satisfaction exponentially. Hence it becomes crucial to understand the crux of the chatbot technology. Owing to extensive research in this field, there are numerous methodologies available to create a conversational entity. It becomes quite confusing to decide a perfect method to generate conversational agent for the desired purpose. Also, generation of chatbot is one issue and successful integration is in itself another problem which is many times overlooked. This paper provides some valuable insights on how to generate as well as how to integrate a chatbot.

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Vatsal Gor

Papers

Chatbot generation and integration: A review