Information Processing and Management - 2023 : Multiheaded Deep Learning Chatbot For Increasing Production And Marketing

Prof. Madya Ts Dr. Zahrah, Yahya (2023) Information Processing and Management - 2023 : Multiheaded Deep Learning Chatbot For Increasing Production And Marketing. Information Processing and Management, 60 (5). pp. 1-14. ISSN 0306-4573

Text 24. Multiheaded Deep Learning Chatbot For Increasing Production And Marketing.pdf Download (4MB)

Abstract

Some businesses on product development prefer to use a chatbot for judging the customer’s view. Today, the ability of a chatbot to consider the context is challenging due to its technical nature. Sometimes, it may misjudge the context, making the wrong decision in predicting the product’s originality in the market. This task of chatbot helps the enterprise make huge profits from ac- curate predictions. However, chatbots may commit errors in dialogs and bring inappropriate responses to users, reducing the confidentiality of product and marketing information. This, in turn, reduces the enterprise gain and imposes cost complications on businesses. To improve the performance of chatbots, AI models are used based on deep learning concepts. This research proposes a multi-headed deep neural network (MH-DNN) model for addressing the logical and fuzzy errors caused by retrieval chatbot models. This model cuts down on the error raised from the information loss. Our experiments extensively trained the model on a large Ubuntu dialog corpus. The recall evaluation scores showed that the MH-DNN approach slightly outperformed selected state-of-the-art retrieval-based chatbot approaches. The results obtained from the MHDNN augmentation approach were pretty impressive. In our proposed work, the MHDNN algorithm exhibited accuracy rates of 94% and 92%, respectively, with and without the help of the Seq2Seq technique.

Item Type:	Article
Uncontrolled Keywords:	Deep neural network Chatbot Business product development Marketing Artificial intelligence
Subjects:	R Medicine > R Medicine (General)
Divisions:	Institute of Graduate Studies (IGS)
Depositing User:	Mrs Shariffah Shuhaiza Syed Mohd Nor
Date Deposited:	26 May 2025 03:43
Last Modified:	26 May 2025 03:43
URI:	http://eprints.kuptm.edu.my/id/eprint/4118

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