AI and Deep Learning-driven Chatbots: A Comprehensive Analysis and Application Trends

Maher, Santosh; Bhable, Suvarnsing G.; Lahase, Ashish R.; Nimbhore, Sunil

doi:10.1109/iciccs53718.2022.9788276

Cited by 12 publications

(1 citation statement)

References 10 publications

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“…Chatbot Helpdesk khususnya adalah jenis Chatbot yang dirancang untuk memberikan dukungan pelanggan dengan menjawab pertanyaan seputar produk atau layanan [2]. Chatbot dikembangkan untuk dapat merespons masukan pengguna secara aktif [3].…”

Section: Pendahuluanunclassified

Improving Helpdesk Chatbot Performance with Term Frequency-Inverse Document Frequency (TF-IDF) and Cosine Similarity Models

Setiawan,

Adnyana

2023

JAIC

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Helpdesk chatbots are growing in popularity due to their ability to provide help and answers to user questions quickly and effectively. Chatbot development poses several challenges, including enhancing accuracy in understanding user queries and providing relevant responses while improving problem-solving efficiency. In this research, we aim to enhance the accuracy and efficiency of the Helpdesk Chatbot by implementing the Term Frequency-Inverse Document Frequency (TF-IDF) model and the Cosine Similarity algorithm. The TF-IDF model is a method used to measure the frequency of words in a document and their occurrence in the entire document collection, while the Cosine Similarity algorithm is used to measure the similarity between two documents. After implementing and testing TF-IDF and Cosine Similarity models in the Helpdesk Chatbot, we achieved a 75% question recognition rate. To increase accuracy and precision, it is necessary to increase the knowledge dataset and improve pre-processing, especially in recognition and correct inaccurate spelling

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Section: Pendahuluanunclassified