A conversational agent (chatbot) is a software that communicates with
people using natural language. Natural language processing and
artificial intelligence rely heavily on conversation modeling.
(AI).Indeed, creating a reliable chatbot system has been one of the most
difficult challenges in AI since its inception. Although this system can
do a variety of things, it must be able to recognize what users are
saying in chat and reply to their questions. As a result, this study
proposes a deep learning Arabic chatbot system built on a deep neural
network model. The proposed method allows for text chats with others
about common topics. The suggested system makes use of a Jordanian
dialect derived from the website of Jordan’s Al-Zaytoonah University.
The model is also created and tested in the deep learning frameworks
Tensorflow and Keras. Furthermore, with no handcrafted rules, a dataset
of manually produced pairs of conversations is used. This leads to the
development of a chat bot system to assist users in counseling via the
Al-Zaytoonah website. While the findings are promising and significant,
the obtained results show that this system is capable of reproducing
efficient and satisfying responses to users for the majority of queries.
It is also demonstrated by the obtained results that an extreme burden
is placed on the admissions department, including less online
utilization of the website.
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