International Journal For Multidisciplinary Research

E-ISSN: 2582-2160     Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 6 Issue 6 November-December 2024 Submit your research before last 3 days of December to publish your research paper in the issue of November-December.

Admission BOT: Unleashing the Potential of Neural Networks in Streamlining the Admission Process

Author(s) Mahendra Uttam Dabhade, D.V. Thombre
Country India
Abstract This paper discuss the problems identified in admission guidance process conducted by the Government Agency where students, parents and other stakeholders of admission do not understand complicated language used in the policy documents and misinformed by the lack of knowledge. This problem can be reduced by the creation and development of an admission Auto-Reply Bot designed to reduce human efforts and provide automated solutions to queries related to admission process.
For this dataset of question and answers are created using information brochure data available in public domain which is conducted by one of the government agency [4]. Different NLP techniques such as tokenization, lemmatization & stemming are applied to the data this data later stored in JSON. Artificial neural network is used to train this dataset. ANN model is trained, Chatbot performed well with selected question set, accuracy of the model increased to 0.9918 using hyper parameters adjustments such as dropout and Adam optimizer.
Keywords Chatbot, Natural Language Processing, Artificial Intelligence, Deep Neural Network, Artificial Neural Network, Admission Queries, Feed forward Network, Admission
Field Computer Applications
Published In Volume 5, Issue 3, May-June 2023
Published On 2023-06-24
Cite This Admission BOT: Unleashing the Potential of Neural Networks in Streamlining the Admission Process - Mahendra Uttam Dabhade, D.V. Thombre - IJFMR Volume 5, Issue 3, May-June 2023. DOI 10.36948/ijfmr.2023.v05i03.3989
DOI https://doi.org/10.36948/ijfmr.2023.v05i03.3989
Short DOI https://doi.org/gsdk6f

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