Chatbots: History, technology, and applications

Adamopoulou, Eleni; Moussiades, Lefteris

doi:10.1016/j.mlwa.2020.100006

Cited by 503 publications

(360 citation statements)

References 48 publications

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“…It has been evidenced that when clients face issues, the chatbot can help find a solution. This simple addition will enhance the user experience and improve customer purchase intentions [33,34].…”

Section: Conclusion Recommendations and Future Workmentioning

confidence: 99%

An Innovative Reflection Based on Critically Applying UX Design Principles

Merritt

Zhao

2021

Journal of Open Innovation: Technology, Market, and Complexity

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Over the past few years, the internet and omni-channel domains have created a new economy that is growing rapidly and shifting the way in which businesses operate due to the influence of technological advancements and innovations. Now customers are embracing technology more than ever, user experience is becoming a crucial factor of the customer journey and remaining competitive in any industry is becoming increasingly difficult due to this. These changes have forced many businesses to rethink their presence, whether this is physically or digitally. In order to gain an understanding of how this should be approached, this paper focuses on demonstrating a critical understanding of innovation theories and concepts, which are utilised to enhance value for business. As well as this, web-based technologies and User Experience (UX) principles will be outlined and applied in order to create an online presence for a prototype supermarket, which will be then be reflected upon against PESTLE factors. From this, an innovative strategy will be formulated and evaluated for a new technology-based product/venture.

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Section: Conclusion Recommendations and Future Workmentioning

confidence: 99%

An Innovative Reflection Based on Critically Applying UX Design Principles

Merritt

Zhao

2021

Journal of Open Innovation: Technology, Market, and Complexity

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“…As numerous companies have started introducing and utilizing chatbots in recent years, various research and development projects have been conducted to improve the functionality of chatbots. Adamopoulou et al [4] introduced the history, technologies, and applications of chatbots, and Cahn [5] proposed the architecture and design of chatbots and the process of chatbot development, thereby presenting guidelines for chatbot researchers and developers to follow. Figure 1 shows the architecture of a typical chatbot.…”

Section: Related Workmentioning

confidence: 99%

KoRASA: Pipeline Optimization for Open-Source Korean Natural Language Understanding Framework Based on Deep Learning

Hwang

Shin

Seo

et al. 2021

Mobile Information Systems

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Since the emergence of deep learning-based chatbots for knowledge services, numerous research and development projects have been conducted in various industries. A high demand for chatbots has drastically increased the global market size; however, the limited functional scalability of open-domain chatbots is a challenge to their application to industries. Moreover, as most chatbot frameworks employ English, it is necessary to create chatbots customized for other languages. To address this problem, this paper proposes KoRASA as a pipeline-optimization method, which uses a deep learning-based open-source chatbot framework to understand the Korean language. KoRASA is a closed-domain chatbot that is applicable across a wide range of industries in Korea. KoRASA’s operation consists of four stages: tokenization, featurization, intent classification, and entity extraction. The accuracy and F1-score of KoRASA were measured based on datasets taken from common tasks carried out in most industrial fields. The algorithm for intent classification and entity extraction was optimized. The accuracy and F1-score were 98.2% and 98.4% for intent classification and 97.4% and 94.7% for entity extraction, respectively. Furthermore, these results are better than those achieved by existing models. Accordingly, KoRASA can be applied to various industries, including mobile services based on closed-domain chatbots using Korean, robotic process automation (RPA), edge computing, and Internet of Energy (IoE) services.

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“…Chatbot is an artificial intelligence programme, which is based on the development of AI, it is hoped that the chatbot's ability to imitate human agents in conversation. Chatbots have become so common in their presence that they can reduce service costs and can handle multiple customers simultaneously [2]. Hopefully, future chatbots can improve business sector performance by increasing customer satisfaction levels by saving time.…”

Section: Introductionmentioning

confidence: 99%

Measuring the accuracy of LSTM and BiLSTM models in the application of artificial intelligence by applying chatbot programme

Anki

Bustamam²

2021

IJEECS

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Python programme contains a question and answer system that derived from data sets that have used and implemented the chatbot in this modern era. where the data collected is in the form of corpuses containing extensive metadata-rich fictional conversations derived from extracted film scripts, commonly called cornell movie dialogue corpus. The various models have been used chatbots in python programmes, and LSTM and BiLSTM models were specifically used in this study. Where the form of accuracy will be reported as a result of the implementation of LSTM and BiLSTM models in the chatbot programme. The programme performance will be influenced by the data from the model selection, because the level of accuracy is determined by the target programme being taken. So this is the main factor that determines which model to choose. Based on considerations required for choosing the programme model, in the end the LSTM and the BiLSTM models are chosen and will be applied to the programme. Based on the LSTM and BiLSTM chatbot programmes that have been tested, it can be concluded that the best parameters come from a pair of BiLSTM chatbots using the BiLTSM model with an average accuracy value of 0.995217.

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Chatbots: History, technology, and applications

Cited by 503 publications

References 48 publications

An Innovative Reflection Based on Critically Applying UX Design Principles

An Innovative Reflection Based on Critically Applying UX Design Principles

KoRASA: Pipeline Optimization for Open-Source Korean Natural Language Understanding Framework Based on Deep Learning

Measuring the accuracy of LSTM and BiLSTM models in the application of artificial intelligence by applying chatbot programme

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