Main Reference PaperBiclustering based Collaborative Filtering Algorithm for Personalized Web Service Recommendation, International Journal of Computer Applications, May 2016 [Java/J2EE].
  • In existing CF algorithms do not consider the existent duality between users and items, it creates the data sparsity problem in further progress. To deal this problem, a collaborative filtering recommendation algorithm is proposed based on biclustering. The biclustering algorithm computes bicluster similarity using Pearson Correlation Coefficient (PCC). Upon bicluster similarity, the most suitable POIs of webservice will be recommended to an active user.

+ Description
  • In existing CF algorithms do not consider the existent duality between users and items, it creates the data sparsity problem in further progress. To deal this problem, a collaborative filtering recommendation algorithm is proposed based on biclustering. The biclustering algorithm computes bicluster similarity using Pearson Correlation Coefficient (PCC). Upon bicluster similarity, the most suitable POIs of webservice will be recommended to an active user.

  • The aim of this project is to recommended a high quality web services to an active user.

  • To improve the recommendation quality.

  • To solve the data sparsity problem.

+ Aim & Objectives
  • The aim of this project is to recommended a high quality web services to an active user.

  • To improve the recommendation quality.

  • To solve the data sparsity problem.

  • 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 J2SE.

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

  • Netbeans 8.0.1 and J2SE.

  • B.E / B.Tech / M.E / M.Tech

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

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