Main Reference PaperCollaborative Filtering Service Recommendation Based on a Novel Similarity Computation Method, IEEE Transactions on Services Computing, 2016 [python].
  • Similarity measurements and prediction of unknown values are two important procedures of memory-based collaborative filtering service recommendation. This paper proposes a ratio-based method to calculate the similarity. The proposed method obtains better prediction precision, lower mean absolute error (MAE) and faster computation time than various reference schemes considered.

Description
  • Similarity measurements and prediction of unknown values are two important procedures of memory-based collaborative filtering service recommendation. This paper proposes a ratio-based method to calculate the similarity. The proposed method obtains better prediction precision, lower mean absolute error (MAE) and faster computation time than various reference schemes considered.

  • To recommend unused services to the user.

  • To improve prediction accuracy.

  • Low computation time.

Aim & Objectives
  • To recommend unused services to the user.

  • To improve prediction accuracy.

  • Low computation time.

  • A technique is contributed to improve the proposed scheme.

Contribution
  • A technique is contributed to improve the proposed scheme.

  • 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-Depending on the complexity of the project and requirements.

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

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