Maria Zafar

Developing Smart Conversation Agent ECOM-BOT for Ecommerce Applications using Deep Learning and Pattern Matching

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Author(s)

Maria Zafar ^1,*

1. Department of Computer Science, Institute of Business Administration, Karachi, Pakistan

* Corresponding author.

DOI: https://doi.org/10.5815/ijieeb.2023.02.01

Received: 2 Nov. 2022 / Revised: 24 Dec. 2022 / Accepted: 2 Feb. 2023 / Published: 8 Apr. 2023

Index Terms

Chatbot, Ecommerce, Pattern matching, Machine learning, Natural dialog interfaces, Natural language processing, Deep Learning

Abstract

Chatbots are a technological leap in conversational services, generating messages to users either following a set of rules to respond based on recognized patterns or training themselves from previous data or conversations. The primary goal is to enable a device to communicate with a user upon receiving natural language user requests using artificial intelligence and machine learning to generate automated responses. Technology is progressively catering to the questions, both in academic and business contexts, such as situations that require agents to investigate the cause of customer dissatisfaction or to recommend products and services. Significance of this research is to reduce the human dependency and improving customer support by providing close to human natural responses using pattern matching and deep learning on the custom-made data. The main objective of this work is to (a) study the existing literature on cutting-edge technologies in chatbot development in terms of research trends, legacy components, techniques, datasets, and domains specifically in e-commerce and (b) to develop a product that fill some of the gaps/missing functionality identified in current frameworks. We have achieved the following, (a) generated small yet generic dataset, which can be used for all types of products, (b) the intents are identified accurately by the bot using deep learning, whenever a user query.

Cite This Paper

Maria Zafar, "Developing Smart Conversation Agent ECOM-BOT for Ecommerce Applications using Deep Learning and Pattern Matching", International Journal of Information Engineering and Electronic Business(IJIEEB), Vol.15, No.2, pp. 1-10, 2023. DOI:10.5815/ijieeb.2023.02.01

Reference

[1] Adamopoulou, Eleni, and Lefteris Moussiades. (2020). “Chatbots: History, technology, and applications.” Machine Learning with Applications 2: 100006.
[2] Bansal, H., & Khan, R. (2018). A review paper on human-computer interaction. International Journal of Advanced Research in Computer Science and Software Engineering,8(53), http://dx.doi.org/10.23956/ijarcsse.v8i4.630.
[3] Khanna, A., Pandey, B., Vashishta, K., Kalia, K., Bhale, P., & Das, T. (2015). A study of today’s A.I. through chatbots and rediscovery of machine intelligence. International Journal of U-and e-Service, Science and Technology,8, 277–284.http://dx.doi.org/10.14257/ijunesst.2015.8.7.28.
[4] Shawar,B.,&Atwell E. (2007). Chatbots: Are they really useful?.LDV Forum,22,29–49
[5] Brandtzaeg, P., & Følstad, A. (2017). Why people use chatbots. In I. Kompatsiaris, & etal.(Eds.),Internet science: Vol.10673.Cham:Springer, http://dx.doi.org/10.1007/978-3-319-70284-1_30
[6] R. Ranoliya, B., Raghuwanshi, N., & Singh, S. (2017). Chatbot for university relatedFAQs. In2017 international conference on advances in computing, communications, and informatics (pp.1525–1530). Udupi. https://doi.org/10.1109/ICACCI.2017.8126057.
[7] Costa, P. C. F. da. (2018). Conversing with personal digital assistants: On gender and artificial intelligence. Journal of Science and Technology of theArts,10(3),http://dx.doi.org/10.7559/citarj.v10i3.563, 2-59–79.
[8] Følstad, A., Bertinussen Nordheim, C., & Alexander Bjørkli, C. (2018). In Bodrunova S.(Ed.),Internet science:vol. 11193,What makes users trust a chatbot for customerservice? an exploratory interview study(pp. 194–208). Cham: Springer, http://dx.doi.org/10.1007/978-3-030-01437-7_16.
[9] Wallace, R. S. (2009). The anatomy of a.l.I.C.e. In R. Epstein, G. Roberts, & G. Beber(Eds.), the quest for the thinking computer(pp. 181–210). Dordrecht: Springer Netherlands, http://dx.doi.org/10.1007/978-1-4020-6710-5_13.
[10] Go, E., & Sundar, S. S. (2019). Humanizing chatbots: The effects of visual, identity and conversational cues on humanness perceptions. Computers in HumanBehavior,97,304–316. http://dx.doi.org/10.1016/j.chb.2019.01.020.

[11] Pamungkas,E.W.(2019). Emotionally-aware chatbots: A survey.ArXiv:1906.09774[Cs]. Retrieved from http://arxiv.org/abs/1906.09774.
[12] Trivedi, A., Gor, V., & Thakkar, Z. (2019). Chatbot generation and integration: A review.International Journal of Advanced Research, Ideas, and Innovations in Technology,5(2),1308–1311, XX.XXX/IJARIIT-V5I2-1840.
[13] Nimavat, K., & Champaneria, T. (2017). Chatbots: An overview of types, architecture, tools, and future possibilities. International Journal for Scientific Research and Development,5(7), 1019–1024, Retrieved from http://www.ijsrd.com/.
[14] Zhang, S., Dinan, E., Urbanek, J., Szlam, A., Kiela, D., & Weston, J. (2018). Personalizing dialogue agents: I have a dog, do you have pets too?. ArXiv:1801.07243 [Cs].Retrieved from http://arxiv.org/abs/1801.07243.
[15] Atwell, E., & Shawar, B. (2003). Using dialogue corpora to train a chatbot. https://doi.org/10.13140/2.1.1455.7122.
[16] Tammewar, A., Pamecha, M., Jain, C., Nagvenkar, A., & Modi, K. (2018).Production-ready chatbots: generate if not retrieve. AAAI Workshops.
[17] Biduski, D., Bellei, E. A., Rodriguez, J., Zaina, L., & Bertoletti De Marchi, A. (2020).Assessing long-term user experience on a mobile health application through an in-app embedded conversation-based questionnaire. Computers in Human Behavior,104, Article 106169. http://dx.doi.org/10.1016/j.chb.2019.106169.15
[18] Baudart, G., Dolby, J., Duesterwald, E., Hirzel, M., & Shinnar, A. (2018). Protecting chatbots from toxic content.(pp.99–110).https://doi.org/10.1145/3276954.3276958.
[19] Schuetzler, R. M., Grimes, G. M., & Giboney, J. S. (2019). The effect of conversational agent skill on user behavior during deception.Computers in Human Behavior,97,250–259. http://dx.doi.org/10.1016/j.chb.2019.03.033.
[20] Bernardini, Andréia & Sônego, Arildo & Pozzebon, Eliane. (2018). Chatbots: An Analysis of the State of Art of Literature. 1. 10.5753/wave.2018.1.
[21] Almansor, Ebtesam & Hussain, Farookh. (2020). Survey on Intelligent Chatbots: State-of-the-Art and Future Research Directions. 10.1007/978-3-030-22354-0_47.
[22] Zevik Farkash. (2018). Chatbots For Ecommerce — 4- ECommerce Challenges and Their Chatbot Solutions, https://medium.com/gobeyond-ai/chatbots-for-ecommerce-4-ecommerce-challenges-and-their-chatbot-solutions-6c8837f3c552
[23] Zevik Farkash. (2019). Ecommerce Chatbot — 4 Challenges Facing Ecommerce And How to Overcome Them Using Chatbots, https://medium.com/gobeyond-ai/chatbots-for-ecommerce-4-ecommerce-challenges-and-their-chatbot-solutions-6c8837f3c552

International Journal of Information Engineering and Electronic Business (IJIEEB)