Collaborative Filtering Recommendation Algorithm Based on Contextual Information
Author(s) -
Jia Guo,
Jianjing Shen
Publication year - 2017
Publication title -
destech transactions on engineering and technology research
Language(s) - English
Resource type - Journals
ISSN - 2475-885X
DOI - 10.12783/dtetr/sste2016/6474
Subject(s) - collaborative filtering , computer science , context (archaeology) , recommender system , process (computing) , information filtering system , curriculum , variable (mathematics) , information retrieval , machine learning , data mining , artificial intelligence , mathematics , biology , pedagogy , psychology , paleontology , mathematical analysis , operating system
Contextual information refers to all the factors affecting the recommendation system and supporting recommendation except “user - item” assessment information. To make effective recommendation to the user against a specific context, it is very important to integrate contextual information into recommendation. Based on contextual information, this paper improves collaborative filtering recommendation algorithm, applying the algorithm to the curricula-variable recommendation context so as to improve the accuracy of recommendation results and provide certain guidance and suggestions to curricula-variable process.
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