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Clustering algorithm is one of the fundamental techniques in data mining, which plays a crucial role in various applications, such as pattern recognition, document retrieval, and computer vision. As so far, many effective algorithms have been proposed. Affinity Propagation is an algorithm requires no parameter indicating the number of clusters, which is the most distinguishing advantage compared to...
With the amount of data increasing rapidly, how to improve the scalability of nonlinear clustering has become a very crucial and challenging problem. In this paper, we design an efficient parallel nonlinear clustering algorithm by using a four-stage MapReduce framework. In our approach, we need to compute two quantities based on distance matrices, which, however, is difficult to compute in a MapReduce...
Transportation data center has recently become a common practice of modern integrated transportation management in major cities of China. Being the convergence center of large-scale multi-source vehicle tracking data, it caused great challenge on GPS map-matching efficiency and privacy protection. In this paper, we propose a secure parallel map-matching system based on Cloud Computing technology to...
As we all know, it is an era of information explosion, in which we always get huge amounts of information. Therefore, it is in urgent need of picking out the useful and interesting information quickly. In order to solve this serious problem, recommendation system arises at the historic moment. Among the existing recommendation algorithms, the item-based collaborative filtering recommendation algorithm...
Map matching (MM), pins the drifting position data to the correct road link on which a vehicle is travelling, is a crucial step needed by many industrial or research ITS projects which rely on post-hoc analysis of trajectories. To address the unprecedented challenge of massive GPS data processing in urban transportation data center nowadays, this paper proposed an improved parallel topological map-matching...
The procedure of matching vehicle location data onto road map is very essential for many ITS (Intelligent Transportation System) applications. However, with the boosting deployment of GPS devices in vehicles, the accumulation of huge amount of GPS data caused great challenge on the efficiency and scalability of traditional serial map matching algorithm. In this paper we address the challenge by presenting...
The boosting deployment of GPS devices in urban vehicles is leading to the collection of large volumes of GPS. Such massive spatial-temporal datasets challenges the efficiency and scalability of the query process during data analysis. In this paper, we introduce the MapReduce framework into the GPS data analysis system. Particularly, we built a graph based bi-level index to accelerate the spatial...
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