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Providing accurate predictions efficiently with privacy is imperative for both customers and e-commerce vendors. However, privacy, accuracy, and performance are conflicting goals. Although producing referrals with privacy is possible; however, online performance and accuracy degrade due to underlying privacy-preserving measures. We investigate how to improve both efficiency and accuracy of naive Bayesian...
Search engines largely rely on web crawlers to collect information from the web. This has led to an enormous amount of web traffic generated by crawlers alone. To minimize negative aspects of this traffic on websites, the behaviors of crawlers may be regulated at an individual web server by implementing the Robots Exclusion Protocol in a file called “robots.txt”. Although not an official standard,...
Many real world phenomena can be naturally modeled as graph structures whose nodes representing entities and whose edges representing interactions or relationships between entities. The analysis of the graph data have many practical implications. However, the release of the data often poses considerable privacy risk to the individuals involved. In this paper, we address the edge privacy problem in...
This paper is concerned with decentralized planning and scheduling where the information for decision making resides within local agents. When considering a decentralized approach, the goal is not primarily on achieving global optimality. For instance, [Greenstadt et al. 2006] studies the tradeoff in the Distributed Constraint Optimization (DCOP) problem on efficiency, privacy and optimality. In principle,...
Collection and analysis of personal information is among the most far-reaching developments in online retail practices. While the potential value of harnessing data about people is expected to improve the online service offerings, it raises reasonable concerns about privacy. Rather than cutting off opportunities to make personal data available for enhancing online services, we introduce a model where...
In this paper we introduce the problem of providing privacy preserving information for Web indexing, classification, and other information retrieval task. Web pages are represented by a frequency term vector that preserves k-anonymity for all the Web pages. This vector can then be used, for example, to build indexes of classifiers. Our proposal makes use of semantic micro aggregation.
Pervasive computing will fundamentally change the way people interact with computers. By observing our actions on an unprecedented scale, the technology will enable new services and applications without the need for direct interaction from the user. However, research has shown that excessive levels of monitoring/data collection can cause undesirable effects on users. Researchers have begun to study...
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