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Movie Recommendation Using OLAP and Multidimensional Data Model

Abstract : This research proposes an adoption of data warehousing concepts to create a movie recommender system. The data warehouse is generated using ETL process in a desired star schema. The profiles of users and movies are created using multidimensional data model. The data are analyzed using OLAP, and the reports are generated using data mining and analysis tools. The recommended movies are selected using multi-criteria candidate selection. The movies which present the genres that match individual preference are recommended to the particular user. The multidimensional data model and OLAP provide high performance to discover the new knowledge in the big data.
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Submitted on : Wednesday, November 30, 2016 - 10:57:58 AM
Last modification on : Wednesday, August 11, 2021 - 7:00:11 PM
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Worapot Jakkhupan, Supasit Kajkamhaeng. Movie Recommendation Using OLAP and Multidimensional Data Model. 13th IFIP International Conference on Computer Information Systems and Industrial Management (CISIM), Nov 2014, Ho Chi Minh City, Vietnam. pp.209-218, ⟨10.1007/978-3-662-45237-0_21⟩. ⟨hal-01405583⟩



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