| Autor: |
Lal, Mily, Neduncheliyan, S. |
| Předmět: |
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| Zdroj: |
Personal & Ubiquitous Computing; Aug2023, Vol. 27 Issue 4, p1483-1494, 12p |
| Abstrakt: |
An artificial intelligence (AI)–based Chatbot system plays a vital role in customer support. In the medical sector, it helps the patients/users get relevant information related to their queries. Although different AI-based Chatbot models have been developed in the past to provide accurate answers to the user, they face some issues. Thus, the novel hybrid Lion-based Deep Belief Chatbot (LbDBC) model is developed in this presented article to support users in retrieving relevant answers related to their queries. Here, the medical QA dataset is considered to validate the designed approach. Incorporating the stemming and tokenization method helps extract root words from the text data. Moreover, the integration of lion fitness provides the finest answer retrieval rate. The presented approach is implemented in Python software version 3.10, and the outcomes are estimated. In addition, a case study is developed to explain the functioning of the designed model. Also, a comparative assessment is produced by comparing the results of the designed model with existing approaches. The comparative assessment verifies that the presented Chatbot model earned better results. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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