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A Novel Recommendation Model Regularized with User Trust and Item Ratings

A Novel Recommendation Model Regularized with User Trust and Item Ratings

Starting at: Rs.5,500.00

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 A Novel Recommendation Model Regularized with User Trust and Item Ratings

 TrustSVD, a trust-based matrix factorization technique for recommendations. TrustSVD integrates multiple information sources into the recommendation model in order to reduce the data sparsity and cold start problems and their degradation of recommendation performance. An analysis of social trust data from four real-world data sets suggests that not only the explicit but also the implicit influence of both ratings and trust should be taken into consideration in a recommendation model. TrustSVD therefore builds on top of a state-of-the-art recommendation algorithm, SVD++ (which uses the explicit and implicit influence of rated items), by further incorporating both the explicit and implicit influence of trusted and trusting users on the prediction of items for an active user. The proposed technique is the first to extend SVD++ with social trust information.


 


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  • Model: PROJ7019
  • 999 Units in Stock
  • Manufactured by: ClickMyProjects

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This product was added to our catalog on Monday 29 May, 2017.

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