Main Reference PaperA User Similarity-based Top-N Recommendation Approach for Mobile In-application Advertising, Expert Systems With Applications, 2018 [R]
  • This work is focus on the user-based neighborhood model for large-scale mobile in-app advertising system. It proposes a top-N recommendation approach (MobRec) that incorporates user clustering and top-N ranking. Users are clustered is based on the mobile context which is gathered on contextual information such as user‘s long-term routine, mobility and device feature.

Description
  • This work is focus on the user-based neighborhood model for large-scale mobile in-app advertising system. It proposes a top-N recommendation approach (MobRec) that incorporates user clustering and top-N ranking. Users are clustered is based on the mobile context which is gathered on contextual information such as user‘s long-term routine, mobility and device feature.

  • Reducing computational complexity.

  • To achieve the scalability

  • To improve the accuracy of top-N recommendation.

Aim & Objectives
  • Reducing computational complexity.

  • To achieve the scalability

  • To improve the accuracy of top-N recommendation.

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

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

  • 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.

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