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Developing a Chatbot Using Machine Learning

04 Aug 2020-Vol. 3, Iss: 8, pp 40-43

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15 Dec 2020
TL;DR: This literature review presents the History, Technology, and Applications of Natural Dialog Systems or simply chatbots, and compose a general architectural design that gathers critical details, and highlights crucial issues to take into account before system design.
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.

24 citations

Proceedings ArticleDOI

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03 Jul 2020
TL;DR: This project aimed to implement online chatbot system to assist users who access college website, using tools that expose Artificial Intelligence methods such as Natural Language Processing, allowing users to communicate with college chatbot using natural language input and to train chat bot using appropriate Machine Learning methods so it will be able to generate a response.
Abstract: The days of solely engaging with a service through a keyboard are over. Users interact with systems more and more through voice assistants and chatbots. A chatbot is a computer program that can converse with humans using Artificial Intelligence in messaging platforms. Every time the chatbot gets input from the user, it saves input and response which helps chatbot with little initial knowledge to evolve using gathered responses. With increased responses, precision of the chatbot also gets increases. The ultimate goal of this project is to add a chatbot feature and API for Matrusri Engineering College. This project will investigate how advancements in Artificial Intelligence and Machine Learning technology are being used to improve many services. Specifically it will look at development of chatbots as a channel for information distribution. The program selects the closest matching response from closest matching statement that matches input utilizing WordNet, it then chooses response from known selection of statements for that response. This project aimed to implement online chatbot system to assist users who access college website, using tools that expose Artificial Intelligence methods such as Natural Language Processing, allowing users to communicate with college chatbot using natural language input and to train chatbot using appropriate Machine Learning methods so it will be able to generate a response. There are numerous applications that are incorporating a human appearance and intending to simulate human dialog, yet in most part of the cases knowledge of chatbot is stored in a database created by a human expert.

3 citations


Cites background from "Developing a Chatbot Using Machine ..."

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Journal ArticleDOI

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21 Feb 2021
TL;DR: Kunci et al. as mentioned in this paper proposed a Chatbot model with Artificial Neural Network (ANN) for web kuliah, which merupakan data pertanyaan sering timbul (Faq) didalam web kULiah yaitu 25 pertanyaa beserta jawaban ying dibagi kedalam 16 label atau kelas.
Abstract: 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.

2 citations

Journal ArticleDOI

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TL;DR: The paper describes overall chatbot architecture and provides corresponding metamodels as well as rules for mapping between the proposed and two commonly used NLU metAModels and could be easily extended with new NLU services and communication channels.
Abstract: In recent years, gradual improvements in communication and connectivity technologies have enabled new technical possibilities for the adoption of chatbots across diverse sectors such as customer services, trade, and marketing. The chatbot is a platform that uses natural language processing, a subset of artificial intelligence, to find the right answer to all users’ questions and solve their problems. Advanced chatbot architecture that is extensible, scalable, and supports different services for natural language understanding (NLU) and communication channels for interactions of users has been proposed. The paper describes overall chatbot architecture and provides corresponding metamodels as well as rules for mapping between the proposed and two commonly used NLU metamodels. The proposed architecture could be easily extended with new NLU services and communication channels. Finally, two implementations of the proposed chatbot architecture are briefly demonstrated in the case study of “ADA” and “COVID-19 Info Serbia”.

1 citations

Proceedings ArticleDOI

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28 Apr 2021
TL;DR: In this paper, a rule based chatbot on a platform named Discord, also showcased that how a chatbot can be integrated into other online platforms to counter the challenges faced in teaching, where Q/A features are used to get in-depth knowledge about various preinstalled data in chatbot.
Abstract: Nowadays, educators can show case the technology of chatbots in various fields such as teaching and learning. Earlier the resources are almost negligible, in the field of education with the learning design integrated in it. But now with the advancement of technology, chatbot can fill the gap in the teaching landscape too. Using chatbot in the education domain is reassuring, since these bots can point out some of the logistics and diversified issues that a normal class might face. Besides this, with the further advancement of Artificial Intelligence, tech-giants like Apple, Google, and Amazon are providing platforms where building conversation is more focused rather than technicalities of computer programming i.e., to be more specific in natural language processing. In this paper, we have built a rule based chatbot on a platform named Discord, also showcased that how a chatbot can be integrated into other online platforms to counter the challenges faced in teaching. Q/A features are used to get in-depth knowledge about various preinstalled data in chatbot.

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