An Embodied Conversational Agent using Retrieval-Based Model and Deep Learning
Pui Huang Leong1, Ong Sing Goh2, Yogan Jaya Kumar3
1Pui Huang Leong, Faculty of Computing and Information Technology, Tunku Abdul Rahman University College (TAR UC), Johor, Malaysia.
2Ong Sing Goh, Centre for Advanced Computing Technology, Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka (UTeM), Melaka, Malaysia.
3Yogan Jaya Kumar, Centre for Advanced Computing Technology, Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka (UTeM), Melaka, Malaysia.
Manuscript received on September 16, 2019. | Revised Manuscript received on 24 September, 2019. | Manuscript published on October 10, 2019. | PP: 4138-4145 | Volume-8 Issue-12, October 2019. | Retrieval Number: L36501081219/2019©BEIESP | DOI: 10.35940/ijitee.L3650.1081219
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In accordance to the Fourth Industrial Revolution, the emergence of the digital transformation alongside with the collaboration between networked machines and human beings in decision-making has attracted much attention globally. The utilization of conversational agent to convey information on behalf of human have gained popularity and been used extensively. As a result, this research intends to examine and to innovate the current corporate website by providing the capabilities to deliver instantaneously replies and reliable information through the integration of a conversational agent via deep learning, comparable to communicating with the competent customer service consultant. This study is reliant on the Artificial Intelligence (AI) to offer natural language processing (NLP) by presenting retrieval-based model and Deep Learning to enable the conversation agent to make smarter and better decision in generating reliable and up-to-date responses. Furthermore, this research intends to automate the process of minimizing the need for human interference, specifically the botmaster to perform the knowledge maintenance manually.
Keywords: Conversational Agent, Retrieval-Based Models, Deep Learning, Artificial Intelligence, Predefined Questions Recommendation.
Scope of the Article: Artificial Intelligence