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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Key-Aggregate Searchable Encryption (KASE) for Group Data Sharing via Cloud Storage

The capability of selectively sharing encrypted data with different users via public cloud storage may greatly ease security concerns over inadvertent data leaks in the cloud. A key challenge to designing such encryption schemes lies in the efficient management of encryption keys. The desired flexibility of sharing any group of selected documents with any group of users demands different encryption keys to be used for different documents. However, this also implies the necessity of securely distributing to users a large number of keys for both encryption and search, and those…

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Neighbor Similarity Trust against Sybil Attack in P2P E-Commerce

Peer to peer (P2P) e-commerce applications exist at the edge of the Internet with vulnerabilities to passive and active attacks. These attacks have pushed away potential business firms and individuals whose aim is to get the best benefit in e-commerce with minimal losses. The attacks occur during interactions between the trading peers as a transaction takes place. How to address Sybil attack is studied, an active attack, in which peers can have bogus and multiple identities to fake their owns. Most existing work, which concentrates on social networks and trusted…

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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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Efficient Filtering Algorithms for Location-Aware Publish/Subscribe

Location-based services have been widely adopted in many systems. Existing works employ a pull model or user-initiated model, where a user issues a query to a server which replies with location-aware answers. To provide users with instant replies, a push model or server-initiated model is becoming an inevitable computing model in the next-generation location-based services. In the push model, subscribers register spatio-textual subscriptions to capture their interests, and publishers post spatio-textual messages. This calls for a high-performance location-aware publish/subscribe system to deliver publishers’ messages to relevant subscribers. The research challenges…

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