z-logo
open-access-imgOpen Access
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.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom