Main Reference PaperExploiting Fine-grained Co-authorship for Personalized Citation Recommendation, IEEE Access, June 2017 [Java/J2EE].
  • Most richest information assisted Graph based model for citation recommendation system is proposed that focuses the non binary Co-authorship fine-grained network model structure, author-paper, paper-citation and paper-keyword relations.

+ Description
  • Most richest information assisted Graph based model for citation recommendation system is proposed that focuses the non binary Co-authorship fine-grained network model structure, author-paper, paper-citation and paper-keyword relations.

  • To generate personalized query oriented recommendation

  • To reduce the information loss using fine-grained model.

+ Aim & Objectives
  • To generate personalized query oriented recommendation

  • To reduce the information loss using fine-grained model.

  • Publication data and author location information are incorporated.

+ Contribution
  • Publication data and author location information are incorporated.

  • Java JDK 1.8, MySQL 5.5.40

  • Netbeans 8.0.1, & J2SE.

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

  • Netbeans 8.0.1, & 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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