RSkNN: kNN Search on Road Networks by Incorporating Social Influence

RSkNN: kNN Search on Road Networks by Incorporating Social Influence DOWNLOAD PROJECT SYNOPSIS Although kNN search on a road network Gr, i.e., finding k nearest objects to a query user q on Gr, has been extensively studied, existing works neglected the fact that the q’s social information can play an important role in this kNN query. Many real-world applications, such as location-based social networking services, require such a query. In this paper we study a new problem: kNN search on road networks by incorporating social influence (RSkNN). Specifically, the state-of-the-art…

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Efficient R-Tree Based Indexing Scheme for Server-Centric Cloud Storage System

Efficient R-Tree Based Indexing Scheme for Server-Centric Cloud Storage System   DOWNLOAD PROJECT SYNOPSIS Cloud storage system poses new challenges to the community to support efficient concurrent querying tasks for various data-intensive applications, where indexes always hold important positions. In this paper, we explore a practical method to construct a two-layer indexing scheme for multi-dimensional data in diverse server-centric cloud storage system. RT-HCN is proposed, which is an indexing scheme integrating R-tree based indexing structure and HCN-based routing protocol. RT-HCN organizes storage and compute nodes into an HCN overlay, one…

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RRW – A Robust and Reversible Watermarking Technique for Relational Data

RRW – A Robust and Reversible Watermarking Technique for Relational Data Advancement in information technology is playing an increasing role in the use of information systems comprising relational databases. These databases are used effectively in collaborative environments for information extraction; consequently, they are vulnerable to security threats concerning ownership rights and data tampering. Watermarking is advocated to enforce ownership rights over shared relational data and for providing a means for tackling data tampering. When ownership rights are enforced using watermarking, the underlying data undergoes certain modifications; as a result of…

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A Large Probabilistic Semantic Network based Approach to Compute Term Similarity

A Large Probabilistic Semantic Network based Approach to Compute Term Similarity Measuring semantic similarity between two terms is essential for a variety of text analytics and understanding applications. Currently, there are two main approaches for this task, namely the knowledge based and the corpus based approaches. However, existing approaches are more suitable for semantic similarity between words rather than the more general multi-word expressions (MWEs), and they do not scale very well. Contrary to these existing techniques, an efficient and effective approach is proposed for semantic similarity using a large…

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Secure Spatial Top-k Query Processing via Untrusted Location-Based Service Providers

Secure Spatial Top-k Query Processing via Untrusted Location-Based Service Providers Collaborative location-based information generation and sharing is considered, which become increasingly popular due to the explosive growth of Internet-capable and location-aware mobile devices. The system consists of a data collector, data contributors, location-based service providers (LBSPs), and system users. The data collector gathers reviews about points-of-interest (POIs) from data contributors, while LBSPs purchase POI data sets from the data collector and allow users to perform spatial top-k queries which ask for the POIs in a certain region and with the…

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t-Closeness through Microaggregation: Strict Privacy with Enhanced Utility Preservation

t-Closeness through Microaggregation: Strict Privacy with Enhanced Utility Preservation Microaggregation is a technique for disclosure limitation aimed at protecting the privacy of data subjects in microdata releases. It has been used as an alternative to generalization and suppression to generate k-anonymous data sets, where the identity of each subject is hidden within a group of k subjects. Unlike generalization, microaggregation perturbs the data and this additional masking freedom allows improving data utility in several ways, such as increasing data granularity, reducing the impact of outliers and avoiding discretization of numerical…

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Real-Time City-Scale Taxi Ridesharing

A taxi-sharing system is proposed and developed that accepts taxi passengers’ real-time ride requests and schedules proper taxis to pick up them via ridesharing, subject to time, capacity, and monetary constraints. The monetary constraints provide incentives for both passengers and taxi drivers: passengers will not pay more compared with no ridesharing and get compensated if their travel time is lengthened due to ridesharing; taxi drivers will make money for all the detour distance due to ridesharing. While such a system is of significant social and environmental benefit, e.g., saving energy…

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Disease Inference from Health-Related Questions via Sparse Deep Learning

Disease Inference from Health-Related Questions via Sparse Deep Learning Automatic disease inference is of importance to bridge the gap between what online health seekers with unusual symptoms need and what busy human doctors with biased expertise can offer. However, accurately and efficiently inferring diseases is non-trivial, especially for community-based health services due to the vocabulary gap, incomplete information, correlated medical concepts, and limited high quality training samples. A user study report is done on the information needs of health seekers in terms of questions and then select those that ask…

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CrowdOp: Query Optimization for Declarative Crowdsourcing Systems

CrowdOp: Query Optimization for Declarative Crowdsourcing Systems To study the query optimization problem in declarative crowdsourcing systems. Declarative crowdsourcing is designed to hide the complexities and relieve the user the burden of dealing with the crowd. The user is only required to submit an SQL-like query and the system takes the responsibility of compiling the query, generating the execution plan and evaluating in the crowdsourcing marketplace. A given query can have many alternative execution plans and the difference in crowdsourcing cost between the best and the worst plans may be…

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Probabilistic Range Query over Uncertain Moving Objects in Constrained Two-Dimensional Space

Probabilistic Range Query over Uncertain Moving Objects in Constrained Two-Dimensional Space Probabilistic range query (PRQ) over uncertain moving objects has attracted much attentions in recent years. Most of existing works focus on the PRQ for objects moving freely in two-dimensional (2D) space. In contrast, this studies the PRQ over objects moving in a constrained 2D space where objects are forbidden to be located in some specific areas. This work dub it the constrained space probabilistic range query (CSPRQ). Its unique properties is analyzed and show that to process the CSPRQ…

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