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Exploiting Semantic Distance In Linked Open Data For Recommendation, Sultan Dawood Alfarhood
Exploiting Semantic Distance In Linked Open Data For Recommendation, Sultan Dawood Alfarhood
Graduate Theses and Dissertations
The use of Linked Open Data (LOD) has been explored in recommender systems in different ways, primarily through its graphical representation. The graph structure of LOD is utilized to measure inter-resource relatedness via their semantic distance in the graph. The intuition behind this approach is that the more connected resources are to each other, the more related they are. One drawback of this approach is that it treats all inter-resource connections identically rather than prioritizing links that may be more important in semantic relatedness calculations. Another drawback of current approaches is that they only consider resources that are connected directly …
Dpweka: Achieving Differential Privacy In Weka, Srinidhi Katla
Dpweka: Achieving Differential Privacy In Weka, Srinidhi Katla
Graduate Theses and Dissertations
Organizations belonging to the government, commercial, and non-profit industries collect and store large amounts of sensitive data, which include medical, financial, and personal information. They use data mining methods to formulate business strategies that yield high long-term and short-term financial benefits. While analyzing such data, the private information of the individuals present in the data must be protected for moral and legal reasons. Current practices such as redacting sensitive attributes, releasing only the aggregate values, and query auditing do not provide sufficient protection against an adversary armed with auxiliary information. In the presence of additional background information, the privacy protection …