BIRCH: an efficient data clustering method for very large databases
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Trajectory clustering with mixtures of regression models
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Emerging scientific applications in data mining
Communications of the ACM - Evolving data mining into solutions for insights
Modern Information Retrieval
Density-Based Clustering in Spatial Databases: The Algorithm GDBSCAN and Its Applications
Data Mining and Knowledge Discovery
CLARANS: A Method for Clustering Objects for Spatial Data Mining
IEEE Transactions on Knowledge and Data Engineering
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Achieving anonymity via clustering
Proceedings of the twenty-fifth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Surface street traffic estimation
Proceedings of the 5th international conference on Mobile systems, applications and services
Mining Frequent Trajectory Patterns for Activity Monitoring Using Radio Frequency Tag Arrays
PERCOM '07 Proceedings of the Fifth IEEE International Conference on Pervasive Computing and Communications
Density-based clustering for real-time stream data
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Query answering techniques on uncertain and probabilistic data: tutorial summary
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Sliding-window top-k queries on uncertain streams
Proceedings of the VLDB Endowment
A Hierarchical Algorithm for Clustering Uncertain Data via an Information-Theoretic Approach
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
HIREL: An Incremental Clustering Algorithm for Relational Datasets
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
Robust Time-Referenced Segmentation of Moving Object Trajectories
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
Clustering Uncertain Data Using Voronoi Diagrams
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
Robust Time-Referenced Segmentation of Moving Object Trajectories
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
Evolutionary Clustering by Hierarchical Dirichlet Process with Hidden Markov State
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
A Framework for Clustering Uncertain Data Streams
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Canopy closure estimates with GreenOrbs: sustainable sensing in the forest
Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems
Traffic density-based discovery of hot routes in road networks
SSTD'07 Proceedings of the 10th international conference on Advances in spatial and temporal databases
A visual analytics system for metropolitan transportation
Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Exploration of ground truth from raw GPS data
Proceedings of the ACM SIGKDD International Workshop on Urban Computing
Proceedings of the ACM SIGKDD International Workshop on Urban Computing
Urban traffic modelling and prediction using large scale taxi GPS traces
Pervasive'12 Proceedings of the 10th international conference on Pervasive Computing
Inferring geographic coincidence in ephemeral social networks
ECML PKDD'12 Proceedings of the 2012 European conference on Machine Learning and Knowledge Discovery in Databases - Volume Part II
Analyzing the workload dynamics of a mobile phone network in large scale events
Proceedings of the first workshop on Urban networking
A data-driven approach for convergence prediction on road network
W2GIS'13 Proceedings of the 12th international conference on Web and Wireless Geographical Information Systems
Adaptive collective routing using gaussian process dynamic congestion models
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
TODMIS: mining communities from trajectories
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Analysis and evaluation of the slugging form of ridesharing
Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Deploying a network of smart cameras for traffic monitoring on a "city kernel"
Expert Systems with Applications: An International Journal
From taxi GPS traces to social and community dynamics: A survey
ACM Computing Surveys (CSUR)
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Identifying hot spots of moving vehicles in an urban area is essential to many smart city applications. The practical research on hot spots in smart city presents many unique features, such as highly mobile environments, supremely limited size of sample objects, and the non-uniform, biased samples. All these features have raised new challenges that make the traditional density-based clustering algorithms fail to capture the real clustering property of objects, making the results less meaningful. In this paper we propose a novel, non-density-based approach called mobility-based clustering. The key idea is that sample objects are employed as "sensors" to perceive the vehicle crowdedness in nearby areas using their instant mobility, rather than the "object representatives". As such the mobility of samples is naturally incorporated. Several key factors beyond the vehicle crowdedness have been identified and techniques to compensate these effects are proposed. We evaluate the performance of mobility-based clustering based on real traffic situations. Experimental results show that using 0.3% of vehicles as the samples, mobility-based clustering can accurately identify hot spots which can hardly be obtained by the latest representative algorithm UMicro.