Yasser Jafer

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With 19%–28% of Internet users participating in online health discussions, it became imperative to be able to detect and analyze posted personal health information (PHI). In this work we introduce two semantic-based methods for mining PHI on social networks which will warn the users about potential privacy breaches. One method uses WordNet as a source of(More)
BACKGROUND Participants in medical forums often reveal personal health information about themselves in their online postings. To feel comfortable revealing sensitive personal health information, some participants may hide their identity by posting anonymously. They can do this by using fake identities, nicknames, or pseudonyms that cannot readily be traced(More)
Protection of patient's privacy is an obligation enforced by laws and regulations in the US, Canada, and other jurisdictions. With exponential growth of exchange of personal health information (PHI) brought about by e-health, there is a need for smart algorithms that help the data publisher to protect PHI. Within exiting privacy models, differential privacy(More)
A large amount of digital information collected and stored in databases creates new opportunities for knowledge discovery and data mining. The datasets, however, may contain personally identifiable information that needs to be protected. With high dimensionality of many large datasets, dimensionality reduction such as feature selection becomes(More)
Feature selection is based on the notion that redundant and/or irrelevant variables bring no additional information about the data classes and can be considered noise for the predictor. As a result, the total feature set of a dataset could be minimized to only few features containing maximum discrimination information about the class. Classification(More)
Data mining is the process of extracting patterns from data. A main step in this process is referred to as data classification. In this work, we investigate the use of the Cell-DEVS formalism for classifying data. The cells in a Cell-DEVS based grid are individually very simple but together they can represent complex behavior and are capable of(More)