Main Reference PaperBayesian-Inference-Based Recommendation in Online Social Networks, IEEE Transactions on Parallel and Distributed Systems, April 2013.
  • Primary aim of this project is to develop a Bayesian-inference based recommendation system for online social networks. The users share their content ratings with friends. The rating similarity between a pair of friends is measured by a set of conditional probabilities derived from their mutual rating history.

+ Description
  • Primary aim of this project is to develop a Bayesian-inference based recommendation system for online social networks. The users share their content ratings with friends. The rating similarity between a pair of friends is measured by a set of conditional probabilities derived from their mutual rating history.

  • To conduct multiple-hop recommendation in online social networks

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

  • To propose the scalable recommendation system in distributed manner.

+ Aim & Objectives
  • To conduct multiple-hop recommendation in online social networks

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

  • To propose the scalable recommendation system in distributed manner.

  • This project proposes one contribution method, that is The probabilistic model based recommendation it will increase therecommendation accuracy. Compare to the Bayesian inference based recommendation provide better accuracy.

  • CONTENT

+ Contribution
  • This project proposes one contribution method, that is The probabilistic model based recommendation it will increase therecommendation accuracy. Compare to the Bayesian inference based recommendation provide better accuracy.

  • 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

  • B.E / B.Tech / M.E / M.Tech

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

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