Main Reference PaperAn Approach for Building Efficient and Accurate Social Recommender Systems using Individual Relationship Networks, IEEE Transactions on Knowledge and Data Engineering, June 2017 [Java/J2EE]
  • An accurate recommendation model is proposed that generates an individual relationship network (IRN) for each user and item using novel fitting algorithm. It generates recommendation by fusing matrix factorization with social regularization and the neighborhood model using IRN’s.

+ Description
  • An accurate recommendation model is proposed that generates an individual relationship network (IRN) for each user and item using novel fitting algorithm. It generates recommendation by fusing matrix factorization with social regularization and the neighborhood model using IRN’s.

  • To improve the efficiency and accuracy of social recommender systems

  • To avoid redundant query responses, to generate an unique id for each query

  • To deal with sparse data and to improve the scalability

+ Aim & Objectives
  • To improve the efficiency and accuracy of social recommender systems

  • To avoid redundant query responses, to generate an unique id for each query

  • To deal with sparse data and to improve the scalability

  • Proposed work is extended with other contextual features

  • CONTENT

+ Contribution
  • Proposed work is extended with other contextual features

  • CONTENT

  • 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

  • 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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