Matrix Factorization with Content Relationships for Media Personalization

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Summary

This paper proposes a novel method, called Content Relationships Matrix Factorization (CRMF), which exploits additional information in the form of content relationships that express relevance between items, which compares favorably to the baseline method, demonstrating the usefulness of considering content relationships.

Type
article
Published
2013-01-01
Cited by
2
References
17
Access
Open access

Keywords

Personalization, Matrix decomposition, Recommender system, Computer science, Exploit

References

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