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Spatial Task Assignment for Crowd Sensing with Cloaked Locations
TLDR
We propose a novel two-stage optimization approach which consists of global optimization using cloaked locations followed by a local optimization using participants' precise locations without breaching privacy. Expand
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Participant Privacy in Mobile Crowd Sensing Task Management: A Survey of Methods and Challenges
TLDR
We identify different task management approaches in mobile crowd sensing, and assess the threats to participant privacy when personal information is disclosed. Expand
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Dynamic Data Driven Crowd Sensing Task Assignment
TLDR
We propose a novel model for spatial task assignment in mobile crowd sensing that uses a dynamic and adaptive data driven scheme to assign moving participants with uncertain trajectories to sensing tasks, in a near-optimal manner. Expand
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A Survey on Privacy in Mobile Crowd Sensing Task Management
Mobile crowd sensing enables a broad range of novel applications by leveraging mobile devices and smartphone users worldwide. While this paradigm is immensely useful, it involves the collection ofExpand
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Privacy Concerns of Semantic Web
TLDR
This paper presents the mandatory role of privacy persevering method in access control model, inference and semantic data mining method and trust negotiation technique for applying in Semantic Web. Expand
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Predict: Privacy and Security Enhancing Dynamic Information Collection and Monitoring
TLDR
In this paper, we present an overview of our ongoing project PREDICT (Privacy and secuRity Enhancing Dynamic Information Collection and moniToring). Expand
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STAC: spatial task assignment for crowd sensing with cloaked participant locations
TLDR
We propose to demonstrate STAC, a tool for spatial task assignment with cloaked locations in crowd sensing applications. Expand
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Help me find a job: A graph-based approach for job recommendation at scale
TLDR
We propose a scalable item-based recommendation system for online job recommendations by leveraging a directed graph of jobs connected by multi-edges representing various behavioral and contextual similarity signals. Expand
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Privacy Preserving Reverse k-Nearest Neighbor Queries
TLDR
Reverse k-nearest neighbor (RkNN) queries are prevalent in location-based services to find those locations that have the query point as one of their k nearest neighbors with reasonable computation and storage overhead. Expand
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Long Tail Query Enrichment for Semantic Job Search
TLDR
In this paper, we propose a method for semantic augmentation of long tail queries in the job search domain using clickthrough and search logs. Expand
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