Main Reference PaperExploring Latent Preferences for Context-Aware Personalized Recommendation Systems, IEEE Transactions on Human-Machine Systems, 2016 [Java/J2EE].
  • This work proposes a recommendation model to identify the latent features of contexts for both users and items. In order to find the latent preferences in recommendation model, it calculate three types of similarities for each individual dimension: user-user, item-item, and context-context. Based upon similar user the most suitable latent context preferences will be recommended to an active user.

+ Description
  • This work proposes a recommendation model to identify the latent features of contexts for both users and items. In order to find the latent preferences in recommendation model, it calculate three types of similarities for each individual dimension: user-user, item-item, and context-context. Based upon similar user the most suitable latent context preferences will be recommended to an active user.

  • To enhance the accuracy of the recommendation.

  • To provide more importance to the individual user’s context, including contextual history.

+ Aim & Objectives
  • To enhance the accuracy of the recommendation.

  • To provide more importance to the individual user’s context, including contextual history.

  • A technique is contributed that improves the accuracy of recommendation algorithm.

+ Contribution
  • A technique is contributed that improves the accuracy of recommendation algorithm.

  • Java JDK 1.8, MySQL 5.5.40.

  • Netbeans 8.0.1 and J2EE.

+ Software Tools & Technologies
  • Java JDK 1.8, MySQL 5.5.40.

  • Netbeans 8.0.1 and J2EE.

  • B.E / B.Tech / M.E / M.Tech

+ Project Recommended For
  • B.E / B.Tech / M.E / M.Tech

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