Main Reference PaperA System to Filter Unwanted Messages from OSN user Walls, Feb 2013.
  • Previous techniques have shown that average OSN users have difficulties in understanding also the simple privacy settings provided by today OSNs. To overcome this problem, a promising trend is to exploit data mining techniques to infer the best privacy preferences to suggest to OSN users, This project ,proposed one system that allowing OSN users to have a direct control on the messages posted on their walls.

+ Description
  • Previous techniques have shown that average OSN users have difficulties in understanding also the simple privacy settings provided by today OSNs. To overcome this problem, a promising trend is to exploit data mining techniques to infer the best privacy preferences to suggest to OSN users, This project ,proposed one system that allowing OSN users to have a direct control on the messages posted on their walls.

  • To give users the ability to control the messages posted on their own private space.

  • To avoid that unwanted content is displayed.

  • To improve the quality of classification.

+ Aim & Objectives
  • To give users the ability to control the messages posted on their own private space.

  • To avoid that unwanted content is displayed.

  • To improve the quality of classification.

  • A flexible rule-based system that allows users to customize the filtering criteria to be applied to their walls, and a Machine Learningbased soft classifier automatically labeling messages in support of content-based filtering. The system exploits a ML soft classifier to enforce customizable content-dependent FRs. Moreover, the flexibility of the system in terms of filtering options is enhanced through the management of BLs.

+ Contribution
  • A flexible rule-based system that allows users to customize the filtering criteria to be applied to their walls, and a Machine Learningbased soft classifier automatically labeling messages in support of content-based filtering. The system exploits a ML soft classifier to enforce customizable content-dependent FRs. Moreover, the flexibility of the system in terms of filtering options is enhanced through the management of BLs.

  • 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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