Maximum Influential Location Selection With Differentially Private User Locations
نویسندگان
چکیده
منابع مشابه
Top-k Most Influential Location Selection
We propose and study a new type of facility location selection query, the top-k most influential location selection query. Given a set M of customers and a set F of existing facilities, this query finds k locations from a set C of candidate locations with the largest influence values, where the influence of a candidate location c (c ∈ C) is defined as the number of customers in M who are the re...
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Privacy-preserving electricity markets have a key role in steering customers towards participation in local electricity markets by guarantying to protect their sensitive information. Moreover, these markets make it possible to statically release and share the market outputs for social good. This paper aims to design a market for local energy communities by implementing Differential Privacy (DP)...
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With the wide adoption of handheld devices (e.g., smartphones, tablets), a large number of location-based services (also called LBSs) have flourished providing mobile users with real-time and contextual information on the move. Accounting for the amount of location information they are given by users, these services are able to track users wherever they go and to learn sensitive information abo...
متن کاملProcessing of Top-K Most Influential Location Selection Queries
Facility location selection queries help to evaluate the popularity of different facility locations for a to-be-added facility. Such queries have wide applications in marketing and decision support systems. In this report, we propose and investigate a new type of queries aiming to retrieve the top-k most influential locations from a candidate set in a given context of customers and existing fac...
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Existing location-based services provide specialized services to their customers based on the knowledge of their exact locations. With untrustworthy servers, location-based services may lead to several privacy threats ranging from worries over employers snooping on their workers’ whereabouts to fears of tracking by potential stalkers. While there exist several techniques to preserve location pr...
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ژورنال
عنوان ژورنال: IEEE Access
سال: 2020
ISSN: 2169-3536
DOI: 10.1109/access.2020.2990706