Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource A Comparative Study of Collaborative Movie Recommendation System Subject The topic of the resource Clustering; Collaborative Filtering; Content-based Filtering; Machine Learning; Movie Recommendation; User ratings Description An account of the resource The number of movies available has expanded, making it challenging to select a film that uses current technology to meet users' needs. Following the widespread use of internet services, recommendation systems have become commonplace. The objective for all recommendation systems now is to employ filtering and clustering algorithms to recommend content users are interested in. Suggestions for a media commodity like movies are offered to consumers by locating user profiles of people with comparable likes which makes users' preferences initially determined to allow them to rate movies of their choosing. After a period of use, the recommender system understands the user and offers films that are more likely to receive higher ratings. A comparison study on the existing models helps to understand future scope and improvements for more personalized models for movie recommendation. In comparison to previous models, the MovieLens dataset gives a dependable model that is exact and delivers more customized movie suggestions. In this paper, an approach to do a detailed study and review the user preferences based on item and content of movies has been made to understand the filtering techniques of the collaborative recommendation system to increase accuracy and give highly rated movies as recommendations to the user is carried and based on the results the recommendation system is built with a content-based filtering technique. 2022 IEEE. Creator An entity primarily responsible for making the resource Joseph A.A.; Nair A.M. Source A related resource from which the described resource is derived Proceedings of the International Conference on Electronics and Renewable Systems, ICEARS 2022, pp. 1579-1583. Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICEARS53579.2022.9752015" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICEARS53579.2022.9752015</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85128953748&amp;doi=10.1109%2FICEARS53579.2022.9752015&amp;partnerID=40&amp;md5=afcfc95e9093b587e9cff824c75e3b31" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85128953748&amp;doi=10.1109%2fICEARS53579.2022.9752015&amp;partnerID=40&amp;md5=afcfc95e9093b587e9cff824c75e3b31</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-166548425-1 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Joseph A.A., Christ (Deemed to Be University), Department of Data Science, India; Nair A.M., Christ (Deemed to Be University), Department of Data Science, India