Comparative study of cloud platforms to develop a Chatbot

Patil, Amit; Marimuthu, K.; A, Nagaraja Rao; Niranchana, R.

doi:10.14419/ijet.v6i3.7628

Cited by 31 publications

(19 citation statements)

References 6 publications

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“…Several things need to be work-out such as how to optimize the capabilities of Travel Chatbot, i.e., the integration of Artificial Intelligence (AI) into the system to provide reliable feedback and predict consumer behavior and increase customer satisfaction. All the transactions using Travel Chatbot must be linked to a Blockchain system to minimize fraud and data falsification [30,[35][36][37][38][39].…”

Section: Discussionmentioning

confidence: 99%

Refilling Knowledge and Intention to Use Travel Chatbot: Indonesian Context

Setiawan¹,

Princes²

2020

Proceedings of the 3rd Asia Pacific Management Research Conference (APMRC 2019)

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Industry 4.0 has touched all sectors of industry, including tourism. The digital world has brought competition to a higher level, and the future is much harder than right now. Previous and recent researchers have tried to seek solutions by making innovations and trying to upgrade their levels by analyzing the quantitative and qualitative data in many ways. One sure thing about upgrading levels is to ensure two-way communication. The biggest mistake for any tourism service is to let the customers wait for the response, which will disappoint the customers, and the customers will find other alternatives. A report in 2017 by Nielsen has shown that today's generation has traveled more than any generation, and the tourism world reacted by creating travel chatbots, which are now part of any tourism activities. With the increasing number of travel chatbots, customers will have abundant but also overlapping information. Data from each travel chatbot might end up giving different outcomes, different features for every app, or misleading information, and this in-return will decrease customer satisfaction. This paper addresses this issue by analyzing the literature data from previous and recent researches and find where the travel chatbots must be patterned by integrating Artificial Intelligence and blockchain. The researchers do a qualitative analysis by sending an online form to three Facebook groups of travelers and asking several questions. The informants were purposively selected. Sixty-five informants interviewed by phone and took three months from July 2019 until the end of September 2019 to collect the data. The general inductive approach was utilized to analyze qualitative data. Overall, the result shows that travel chatbots are perceived positively, although the level of knowledge Indonesian traveler for travel chatbot still below 40%. Travel companies will benefit from this paper to understand customer needs in creating the best serving travel chatbots for better services.

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Section: Discussionmentioning

confidence: 99%

Refilling Knowledge and Intention to Use Travel Chatbot: Indonesian Context

Setiawan¹,

Princes²

2020

Proceedings of the 3rd Asia Pacific Management Research Conference (APMRC 2019)

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“…In order to automate conversational processes, human experts need to structure conversations in decision trees that display every possible follow-up question and possible answers to those questions [10,17]. After releasing a chatbot into the live system, the human user can interact with it via a user interface (UI), such as a popup window integrated on a website [17], Facebook Messenger, Skype or Slack [15]. Thereby, a chatbot is able to gather knowledge during each interaction with a human user and improve its accuracy of mapping incoming questions to correct answers within a corresponding decision tree [12,17].…”

Section: Background Literature and Theoretical Foundationmentioning

confidence: 99%

“…Suitable processes for automation should be rule-based, non-complex, standardized and executed in high volumes [2,8,10,17,21,24]. The development of both systems usually requires no in-depth programming knowledge, but rather processes can be graphically modeled within the respective system [15,20,24]. However, before processes can be automated through the development of the respective robots, appropriate process knowledge has to be acquired [10,17,21].…”

Section: Background Literature and Theoretical Foundationmentioning

confidence: 99%

Mastering Software Robot Development Projects: Understanding the Association between System Attributes & Design Practices

Rutschi¹,

Dibbern²

2019

Proceedings of the Annual Hawaii International Conference on System Sciences

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Software robots tend to increasingly take over organizational processes. However, little is known about principles of developing as opposed to using robotic systems, such as RPA robots and chatbots. Therefore, based on a comparative case study, this paper elaborates how different types of robots, due to distinguishing system attributes, relate to different design practices that arise from varying challenges of transforming existing routines into robots.

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“…However, for natural language processing ability, the development of chatbot is an arduous task. Chatbots are applicable in many fields such as in education, traveling, real estate, internet, gaming, education, ecommerce, hospitality and health, call centers, media, financial bot insurance banks, business, traveling customer service and in shopping [4][5][6] 2 .…”

mentioning

confidence: 99%

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2019

Review of Information Engineering and Applications

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A chatbot system enables communication between computer and users through natural language. The university students face many problems for the queries and details regarding their examination and it is also difficult for them to physically visit the examination department frequently. The concerned authorities find it challenging to handle thousands of student queries in parallel, thus, consuming a lot of time. At present, majority of the chatbot system are available in English language. Therefore, people who are not fluent in English language cannot use these systems due to the obvious reason of language barrier. This paper focuses on the viability of a chatbot system for the examination department of Mehran University of Engineering Technology (MUET) Jamshoro. The chatbot discussed in this paper has been designed to support both Urdu and English languages. Three chatbot interfaces have been developed, Urdu typing based chatbot, English typing based chatbot and English voice based Chabot. The typing based chatbots (both English and Urdu) have been developed using AIML, and voice based chatbot is based on dialogflow called as API.ai. This study is not only concerned with the development of three interfaces of chatbot systems, but also covers their evaluation. To find best chatbot interface, a survey was conducted with engineering students of MUET Jamshoro. The results revealed that the among the three chatbot interfaces, English typing-based interface is the best due to the usability, easiness and the general understanding of queries.Contribution/Originality: This paper contribution is twofold, first is the development of a chatbot system that enables communication in Urdu and English languages. Second is the comparison of both chatbots by performing the user testing. INTRODUCTIONWorldwide various chat systems are available that enable communication using natural languages. These chat systems are broadly categorized into two main types namely, Human-Human Dialog System and Human-Computer Dialog System. There is not any involvement of machine learning in Human-Human Dialog System and this work as a negotiator between two humans. The Human-Human Dialog System doesn"t require natural processing abilities through machines. Globally, WhatsApp and skype are the most popular Human-Human Dialog chat system. However, the other available chat system, the Human-Computer Dialog System is termed as chatbot [1].Basically, chatbot is a computer program that pretends chat with humans through natural language [1, 2]. On any platform like mobile, website and desktop application, this system can interact with the humans [3]. While

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Comparative study of cloud platforms to develop a Chatbot

Cited by 31 publications

References 6 publications

Refilling Knowledge and Intention to Use Travel Chatbot: Indonesian Context

Refilling Knowledge and Intention to Use Travel Chatbot: Indonesian Context

Mastering Software Robot Development Projects: Understanding the Association between System Attributes & Design Practices

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