| dc.contributor.author | Li, Qingrui | |
| dc.description.abstract | Privacy protection is a vital issue for safe social interactions within social
networking sites (SNS). Although SNSs such as MySpace and Facebook allow
users to configure their privacy settings, the task is difficult for normal users with
hundreds of online friends. In this paper, I propose an intelligent semantics-based
privacy configuration system, named SPAC, to automatically recommend privacy
settings for SNS users. SPAC learns users’ privacy configuration patterns and make
predictions by utilizing machine learning techniques on users’ profiles and privacy
setting history. To increase the accuracy of the predicted privacy settings,
especially in the context of heterogeneous user profiles, I enhance privacy
configuration predictor by integrating it with structured semantic knowledge. This
allows SPAC to make inferences based on additional source of knowledge,
resulting in improved accuracy of privacy recommendation. Our experimental
results have proven the effectiveness of our approach. | en_US |
| dc.publisher | North Dakota State University | en_US |
| dc.rights | NDSU Policy 190.6.2 | |
| dc.title | Semantics-Enhanced Privacy Recommendation for Social Networking Sites | en_US |
| dc.type | Master's paper | en_US |
| dc.date.accessioned | 2012-07-02T18:15:01Z | |
| dc.date.available | 2012-07-02T18:15:01Z | |
| dc.date.issued | 2012 | |
| dc.identifier.uri | http://hdl.handle.net/10365/21618 | |
| dc.subject.lcsh | Nearest neighbor analysis (Statistics) | en_US |
| dc.subject.lcsh | Ontologies (Information retrieval) | en_US |
| dc.subject.lcsh | Online social networks -- Security measures. | en_US |
| dc.rights.uri | https://www.ndsu.edu/fileadmin/policy/190.pdf | |
| ndsu.degree | Master of Science (MS) | en_US |
| ndsu.college | Engineering | en_US |
| ndsu.department | Computer Science | en_US |
| ndsu.program | Computer Science | en_US |
| ndsu.advisor | Li, Juan | |
