Main Reference Paperl-Injection: Toward Effective Collaborative Filtering Using Uninteresting Items, IEEE Transactions on Knowledge and Data Engineering, April 2017 [R].
  • The accuracy of top-N recommendation is improved by solving the one-class collaborative filtering (OCCF) problem in which uninteresting items are identified low values are injected to them and it is named as l-injection with classification of user preferences into pre-use and post-use preferences.

Description
  • The accuracy of top-N recommendation is improved by solving the one-class collaborative filtering (OCCF) problem in which uninteresting items are identified low values are injected to them and it is named as l-injection with classification of user preferences into pre-use and post-use preferences.

  • To address the sparsity problem of recommender system.

  • To improve CF based algorithms.

Aim & Objectives
  • To address the sparsity problem of recommender system.

  • To improve CF based algorithms.

  • Other context information are incorporated to improve accuracy further.

Contribution
  • Other context information are incorporated to improve accuracy further.

  • M.E / M.Tech/ MS / Ph.D.- Customized according to the client requirements.

Project Recommended For
  • M.E / M.Tech/ MS / Ph.D.- Customized according to the client requirements.

  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

Order To Delivery
  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

Professional Ethics: We S-Logix would appreciate the students those who willingly contribute with atleast a line of thinking of their own while preparing the project with us. It is advised that the project given by us be considered only as a model project and be applied with confidence to contribute your own ideas through our expert guidance and enrich your knowledge.

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