Designing a Web-Based Light Novel Application with an LLM-Powered Chatbot Recommendation System Using Scrum Methodology
DOI:
https://doi.org/10.46880/jmika.Vol8No2.pp174-186Keywords:
Chatbot, Conversational Recommender System, Retrieval Augmented Generation, Scrum, Vector DatabaseAbstract
In the era of the internet’s exponential growth, readers are often overwhelmed by the plethora of books available, particularly in the genre of light novels. This research aims to address this issue by developing a recommendation system for light novels, utilizing a chatbot interface. The methodology employed follows the Borg and Gall model, with a focus on research, information collection, planning, and development stages. The research stage involved the use of questionnaires to gather data and analyze the parameters to be used in the recommendation system. The development stage was carried out using the Scrum methodology and the Retrieval Augmented Generation (RAG) approach for the chatbot’s functionality. The outcome of this study is a web-based online light novel application and featuring a chatbot conversational recommender system. Through this system, users can access and read light novels online, while also utilizing the chatbot to request novel recommendations. The research findings demonstrate the successful integration of Large Language Model (LLM) technology into the web-based light novel application. The Scrum development approach facilitated efficient system creation, and the RAG-based chatbots are seen as successful in producing recommendations that match user queries based on existing knowledge. Recommendation results are obtained from semantic search and from the ranking vector with the highest score.
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