What is it about?
This paper is about an all in one approach for an industrial level implementation of a recommendation system by applying different recommendation approaches, studying and making a comparison with the state of the art and proper implementation which can be a prototype on an industrial level. In this paper we describe the usage of a hybrid weightage based recommender system focused on books and putting a model into the most used platform application. To make it available for the book readers by making an all in one approach to improvise the state of the art and resolve the cold start problem, making the user experience a major standard for the recommendations. The paper deals with the phases of Software Engineering from the analysis of the requirements, the actual making of the recommender model to deployment and testing of the Application at the user end.
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Why is it important?
This paper addresses the critical need for an industrial-level recommendation system for book enthusiasts, integrating diverse recommendation approaches to enhance user experience while resolving the cold start problem. It underscores the significance of comprehensive software engineering phases, from requirement analysis to deployment, in achieving an all-in-one solution for personalized book recommendation
Perspectives
This paper aims to revolutionize book recommendation systems by integrating diverse approaches and prioritizing user experience, emphasizing the importance of thorough software engineering processes for successful deployment in an industrial setting.
Dr. Debajyoty Banik
Read the Original
This page is a summary of: Fabula: Hybridized Weightage Based Book Recommendation System, January 2021, Springer Science + Business Media,
DOI: 10.1007/978-3-030-91305-2_14.
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