%0 Conference Proceedings
%T Movie Recommendation Using OLAP and Multidimensional Data Model
%+ Prince of Songkla University (PSU)
%A Jakkhupan, Worapot
%A Kajkamhaeng, Supasit
%Z Part 4: Data Analysis and Information Retrieval
%< avec comité de lecture
%( Lecture Notes in Computer Science
%B 13th IFIP International Conference on Computer Information Systems and Industrial Management (CISIM)
%C Ho Chi Minh City, Vietnam
%Y Khalid Saeed
%Y Václav Snášel
%I Springer
%3 Computer Information Systems and Industrial Management
%V LNCS-8838
%P 209-218
%8 2014-11-05
%D 2014
%R 10.1007/978-3-662-45237-0_21
%K Movie recommender system
%K Data warehousing
%K MDX language
%K OLAP
%K Multidimensional data model
%Z Computer Science [cs]
%Z Humanities and Social Sciences/Library and information sciencesConference papers
%X 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.
%G English
%Z TC 8
%2 https://inria.hal.science/hal-01405583/document
%2 https://inria.hal.science/hal-01405583/file/978-3-662-45237-0_21_Chapter.pdf
%L hal-01405583
%U https://inria.hal.science/hal-01405583
%~ SHS
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-TC
%~ IFIP-TC8
%~ IFIP-LNCS-8838
%~ IFIP-CISIM