Bufete, Niño V. creator author. Martinez, Daniel L. author Panambo, Erica Mae A. author Piaña, Jeric R. author Santillan, Karra Caye S. author Fortuno, Kaela Marie N., adviser Onesa, Rosel O., panelist, chair Benosa, Brenda Dy-Po, panelist Ramizares, Maricris L., panelist text bibliography ph 2023 monographic eng

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103 leaves. Helpdesks are typically used to troubleshoot customer issues within your organization. Processing user request for another user support through a ticketing system component that businesses must offer to its customers. The classification process for this ticket classifier system's unstructured noisy data set is an important duty. Transformer model is built using an empirically developed methodology that includes the training ticket datasets, ticket data pre-processing, and machine learning algorithm tuning. RNN methods the first word and enters the results back into the layer that performs the next word. This procedure ensures customer satisfaction while also keeping customers informed. There is a great deal of confusion regarding the categories into which text sentences will be thrown with a high probability based on the user's input. Normal, medium, and high. The researchers used RNN to identify the text input of the user requesting assistance. This paper proposes a user-friendly helpdesk built with the flask framework that can accept user messages. This could only be achieved by combining the RNN and transformer models. The paper primarily addresses user messages based on their urgency and concerns. Niño V. Bufete, [and 4 others]. Undergraduate Theses (BSCS) - Computer Science Camarines Sur Polytechnic Colleges, 2023. Includes bibliographical references. CSPC 240123 20240123102550.0 eng