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Movie recommendation using OLAP and multidimensional data model

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2014) 8838 209-218
DOI: 10.1007/978-3-662-45237-0_21
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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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APA

Jakkhupan, W., & Kajkamhaeng, S. (2014). Movie recommendation using OLAP and multidimensional data model. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8838, pp. 209–218). Springer Verlag. https://doi.org/10.1007/978-3-662-45237-0_21

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