Trust Based Novel Recommendation Regularized with Item Ratings
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2017, Vol 5, Issue 4
Abstract
Recommendation is an opinion given by an analyst to his/her client whether the given stock is worth buying or a particular place is worth visiting or not. They use various projections as a basis for issuing recommendations. Item rating is a group of classifications designed to extract information about a quantitative or qualitative attribute. Here we use a scale to reflect the quality of product where user selects the number which is taken into consideration. In order to enhance the novel recommendation model, we propose a trust based recommendation model with item rating where data sparsity and cold start problem are rectified.We make use of personalized social networking to connect people in a commodity so that people can get to know about a product or place in detail by the information shared about it and the user can sort out things according to their needs and specification.
Authors and Affiliations
R. Priyadharshini, J. Subathra, Nivedita K. M, S. Aravinda Krishnan
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