Chengyang Zhang

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GPS-equipped taxis can be regarded as mobile sensors probing traffic flows on road surfaces, and taxi drivers are usually experienced in finding the fastest (quickest) route to a destination based on their knowledge. In this paper, we mine smart driving directions from the historical GPS trajectories of a large number of taxis, and provide a user with the(More)
<i>Map-matching</i> is the process of aligning a sequence of observed user positions with the road network on a digital map. It is a fundamental pre-processing step for many applications, such as moving object management, traffic flow analysis, and driving directions. In practice there exists huge amount of low-sampling-rate (e.g., one point every 2--5(More)
Matching a raw GPS trajectory to roads on a digital map is often referred to as the Map Matching problem. However, the occurrence of the low-sampling-rate trajectories (e.g. one point per 2 minutes) has brought lots of challenges to existing map matching algorithms. To address this problem, we propose an Interactive Voting-based Map Matching (IVMM)(More)
An important privacy issue in Location Based Services(LBS) is to hide a user’s identity while still provide quality location based services. Previous work has addressed the problem of locational K-anonymity either based on centralized or decentralized schemes. However, a centralized scheme relies on an anonymizing server(AS) for location cloaking, which may(More)
Wireless sensor networks (WSNs) have great potential to revolutionize many science and engineering domains. We present a novel environmental monitoring system with a focus on overall system architecture for seamless integration of wired and wireless sensors for longterm, remote, and near-real-time monitoring. We also present a unified framework for sensor(More)
Wireless sensor networks (WSN) technology has great potential to revolutionize many science and engineering domains. We present a novel environmental monitoring system with a focus on the overall system architecture for seamless integration of wired and wireless sensors for long-term, remote, and near-real-time monitoring. We also present a unified(More)
The goal of spatial co-location pattern mining is to find subsets of spatial features frequently located together in spatial proximity. Example co-location patterns include services requested frequently and located together from mobile devices (e.g., PDAs and cellular phones) and symbiotic species in ecology (e.g., Nile crocodile and Egyptian plover).(More)
Article history: Received 6 July 2010 Received in revised form 3 May 2011 Accepted 16 June 2011 Available online 7 July 2011 This paper presents a study of the Multi-Type Reverse Nearest Neighbor (MTRNN) query problem. Traditionally, a reverse nearest neighbor (RNN) query finds all the objects that have the query point as their nearest neighbor. In(More)