Local Suppression and Splitting Techniques for Privacy Preserving Publication of Trajectories

Local Suppression and Splitting Techniques for Privacy Preserving Publication of Trajectories We study the problem of preserving user privacy in the publication of location sequences. Consider a database of trajectories, corresponding to movements of people, captured by their transactions when they use credit cards, RFID debit cards, or NFC compliant devices. We show that, if such trajectories are published exactly (by only hiding the identities of persons that followed them), one can use partial trajectory knowledge as a quasi-identifier for the remaining locations in the sequence. We devise four intuitive…

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Personal Web Revisitation by Context and Content Keywords with Relevance Feedback

Personal Web Revisitation by Context and Content Keywords with Relevance Feedback Getting back to previously viewed web pages is a common yet uneasy task for users due to the large volume of personally accessed information on the web. This paper leverages human’s natural recall process of using episodic and semantic memory cues to facilitate recall, and presents a personal web revisitation technique called WebPagePrev through context and content keywords. Underlying techniques for context and content memories’ acquisition, storage, decay, and utilization for page re-finding are discussed. A relevance feedback mechanism…

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Crowdsourced Coverage as a Service: Two-Level Composition of Sensor Cloud Services

Crowdsourced Coverage as a Service: Two-Level Composition of Sensor Cloud Services A new two-level composition model for crowdsourced Sensor-Cloud services is proposed based on dynamic features such as spatio-temporal aspects. The proposed approach is defined based on a formal Sensor-Cloud service model that abstracts the functionality and non-functional aspects of sensor data on the cloud in terms of spatio-temporal features. A spatio-temporal indexing technique based on the 3D R-tree to enable fast identification of appropriate Sensor-Cloud services is proposed. A novel quality model is introduced that considers dynamic features of…

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Energy-efficient Query Processing in Web Search Engines

Energy-efficient Query Processing in Web Search Engines Web search engines are composed by thousands of query processing nodes, i.e., servers dedicated to process user queries. Such many servers consume a significant amount of energy, mostly accountable to their CPUs, but they are necessary to ensure low latencies, since users expect sub-second response times . However, users can hardly notice response times that are faster than their expectations. Hence, we propose the Predictive Energy Saving Online Scheduling Algorithm (PESOS ) to select the most appropriate CPU frequency to process a query…

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