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In this paper, we aim to mine turn delay at different times and turn types in city road network based on personal GPS collected trajectories. We provide a method to effectively solve the problem for computing turn delay. By using this method, we can rapidly process massive trajectory data, to explore and predict turn delay in city road network. Through(More)
In this paper, we presented a technical framework to calculate the turn delays on road network with floating car data (FCD). Firstly the original FCD collected with GPS equipped taxies was cleaned and matched to a street map with a distributed system based on Hadoop and MongoDB. Secondly the refined dataset was distributed and matched to the specific(More)
Current moving-object database (MOD) systems focus on management of movement data, but pay less attention to modelling social relationships between moving objects and spatial-temporal trajectories in an integrated manner. This paper combines moving-object database and social network systems and presents a novel data model called Geo-Social-Moving (GSM) that(More)
Existing data models for moving objects in networks are often limited by flexibly controlling the granularity of representing networks and the cost of location updates and do not encompass semantic information, such as traffic states, traffic restrictions and social relationships. In this paper, we aim to fill the gap of traditional network-constrained(More)
The rapid growth of location-based services has motivated the development of continuous range queries in networks. Existing query algorithms usually adopt an expansion tree to reuse the previous query results to get better efficiency. However, the high maintenance costs of the traditional expansion tree lead to a sharp efficiency decrease. In this paper, we(More)
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