%0 Conference Proceedings
%T Language Model-Driven Chatbot for Business to Address Marketing and Selection of Products
%+ Indian Institute of Technology Delhi (IIT Delhi)
%A Kushwaha, Amit, Kumar
%A Kar, Arpan, Kumar
%Z Part 1: Artificial Intelligence and Autonomous Systems
%< avec comité de lecture
%( IFIP Advances in Information and Communication Technology
%B International Working Conference on Transfer and Diffusion of IT (TDIT)
%C Tiruchirappalli, India
%Y Sujeet K. Sharma
%Y Yogesh K. Dwivedi
%Y Bhimaraya Metri
%Y Nripendra P. Rana
%I Springer International Publishing
%3 Re-imagining Diffusion and Adoption of Information Technology and Systems: A Continuing Conversation
%V AICT-617
%N Part I
%P 16-28
%8 2020-12-18
%D 2020
%R 10.1007/978-3-030-64849-7_3
%K Artificial intelligence
%K Chatbots
%K Language modeling
%K NLP
%K Deep learning
%K Reinforcement learning
%K Marketing
%Z Computer Science [cs]
%Z Humanities and Social Sciences/Library and information sciencesConference papers
%X Artificial Intelligence has been increasingly gaining acceptance across advanced functions in numerous fields and industries. This includes marketing, customer support, and leads generation in healthcare, transportation, education, and off late in e-commerce. Machine learning as a subset of artificial intelligence techniques provides various algorithms that enable machines to learn from historical data and make realtime predictions on numbers and texts. Most of the businesses nowadays are trying to increase their reach and making sure that they are available to cater to the customers when they need help. This also enables the companies to market and respond to the queries of potential customers on a realtime basis. Chatter robots or chatbot is one such application of machine learning which allows the business to provide round the clock support to customers and potential leads for marketing questions. Most of the business fail to venture in the domain of hosting chatbot on the website as they do not have enough conversational data with them to train the machine learning algorithm and wait for years to collect enough sample. With the proposed language model-driven chatbots, businesses starting fresh in the domain of the hosting this application can use the user-generated content on social media to fuel the backend framework for the chatbots and start hosting the application.
%G English
%Z TC 8
%Z WG 8.6
%2 https://inria.hal.science/hal-03701807/document
%2 https://inria.hal.science/hal-03701807/file/497052_1_En_3_Chapter.pdf
%L hal-03701807
%U https://inria.hal.science/hal-03701807
%~ SHS
%~ IFIP
%~ IFIP-AICT
%~ IFIP-TC
%~ IFIP-WG
%~ IFIP-TC8
%~ IFIP-TDIT
%~ IFIP-WG8-6
%~ IFIP-AICT-617