Efficient mutual nearest neighbor query processing for moving object trajectories

Given a set D of trajectories, a query object q, and a query time extent @C, a mutual (i.e., symmetric) nearest neighbor (MNN) query over trajectories finds from D, the set of trajectories that are among the k"1 nearest neighbors (NNs) of q within @C, and meanwhile, have q as one of their k"2 NNs. This type of queries is useful in many applications such as decision making, data mining, and pattern recognition, as it considers both the proximity of the trajectories to q and the proximity of q to the trajectories. In this paper, we first formalize MNN search and identify its characteristics, and then develop several algorithms for processing MNN queries efficiently. In particular, we investigate two classes of MNN queries, i.e., MNN"P and MNN"T queries, which are defined with respect to stationary query points and moving query trajectories, respectively. Our methods utilize the batch processing and reusing technology to reduce the I/O cost (i.e., number of node/page accesses) and CPU time significantly. In addition, we extend our techniques to tackle historical continuous MNN (HCMNN) search for moving object trajectories, which returns the mutual nearest neighbors of q (for a specified k"1 and k"2) at any time instance of @C. Extensive experiments with real and synthetic datasets demonstrate the performance of our proposed algorithms in terms of efficiency and scalability.

[1]  Dimitrios Gunopulos,et al.  On indexing mobile objects , 1999, PODS '99.

[2]  Walid G. Aref,et al.  Spatio-Temporal Access Methods , 2003, IEEE Data Eng. Bull..

[3]  Chris Jermaine,et al.  Closest-Point-of-Approach Join for Moving Object Histories , 2006, 22nd International Conference on Data Engineering (ICDE'06).

[4]  Yufei Tao,et al.  Continuous Nearest Neighbor Search , 2002, VLDB.

[5]  Dieter Pfoser,et al.  Novel Approaches in Query Processing for Moving Object Trajectories , 2000, VLDB 2000.

[6]  G. Krishna,et al.  Agglomerative clustering using the concept of mutual nearest neighbourhood , 1978, Pattern Recognit..

[7]  Jae-Gil Lee,et al.  Trajectory Outlier Detection: A Partition-and-Detect Framework , 2008, 2008 IEEE 24th International Conference on Data Engineering.

[8]  Yannis Manolopoulos,et al.  Performance of Nearest Neighbor Queries in R-Trees , 1997, ICDT.

[9]  Changshui Zhang,et al.  Clustering in Knowledge Embedded Space , 2003, ECML.

[10]  Petko Bakalov,et al.  Continuous Spatiotemporal Trajectory Joins , 2008, GSN.

[11]  Yufei Tao,et al.  Multidimensional reverse kNN search , 2007, The VLDB Journal.

[12]  Lei Chen,et al.  Robust and fast similarity search for moving object trajectories , 2005, SIGMOD '05.

[13]  Ada Wai-Chee Fu,et al.  Enhanced nearest neighbour search on the R-tree , 1998, SGMD.

[14]  Nick Roussopoulos,et al.  K-Nearest Neighbor Search for Moving Query Point , 2001, SSTD.

[15]  Chaman L. Sabharwal,et al.  A scalable constraint-based Q-hash indexing for moving objects , 2008, Inf. Sci..

[16]  Lien Fa Lin,et al.  Continuous nearest neighbor search , 2008 .

[17]  Yunjun Gao,et al.  Efficient Algorithms for Historical Continuous k NN Query Processing over Moving Object Trajectories , 2007, APWeb/WAIM.

[18]  Yu Qian,et al.  Discovering spatial patterns accurately with effective noise removal , 2004, DMKD '04.

[19]  Yannis Theodoridis,et al.  On the Generation of Spatiotemporal Datasets , 1999 .

[20]  Kyriakos Mouratidis,et al.  Conceptual partitioning: an efficient method for continuous nearest neighbor monitoring , 2005, SIGMOD '05.

[21]  Christian S. Jensen,et al.  Nearest and reverse nearest neighbor queries for moving objects , 2006, The VLDB Journal.

[22]  B. C. Brookes,et al.  Information Sciences , 2020, Cognitive Skills You Need for the 21st Century.

[23]  G. Krishna,et al.  The condensed nearest neighbor rule using the concept of mutual nearest neighborhood (Corresp.) , 1979, IEEE Trans. Inf. Theory.

[24]  Anthony K. H. Tung,et al.  Ranking Outliers Using Symmetric Neighborhood Relationship , 2006, PAKDD.

[25]  Dimitrios Gunopulos,et al.  Discovering similar multidimensional trajectories , 2002, Proceedings 18th International Conference on Data Engineering.

[26]  Nick Roussopoulos,et al.  Nearest neighbor queries , 1995, SIGMOD '95.

[27]  Walid G. Aref,et al.  SEA-CNN: scalable processing of continuous k-nearest neighbor queries in spatio-temporal databases , 2005, 21st International Conference on Data Engineering (ICDE'05).

[28]  Roberto Tamassia,et al.  Continuous probabilistic nearest-neighbor queries for uncertain trajectories , 2009, EDBT '09.

[29]  Anthony J. T. Lee,et al.  Mining frequent trajectory patterns in spatial-temporal databases , 2009, Inf. Sci..

[30]  Tetsuji Satoh,et al.  Shape-Based Similarity Query for Trajectory of Mobile Objects , 2003, Mobile Data Management.

[31]  Hanan Samet,et al.  Distance browsing in spatial databases , 1999, TODS.

[32]  Marios Hadjieleftheriou,et al.  Efficient trajectory joins using symbolic representations , 2005, MDM '05.

[33]  Xiaohui Yu,et al.  Monitoring k-nearest neighbor queries over moving objects , 2005, 21st International Conference on Data Engineering (ICDE'05).

[34]  Jianwen Su,et al.  One Way Distance: For Shape Based Similarity Search of Moving Object Trajectories , 2008, GeoInformatica.

[35]  Yunjun Gao,et al.  On efficient mutual nearest neighbor query processing in spatial databases , 2009, Data Knowl. Eng..

[36]  Jesús Manuel Almendros-Jiménez,et al.  A performance comparison of distance-based query algorithms using R-trees in spatial databases , 2007, Inf. Sci..

[37]  Hanan Samet,et al.  Continuous K-Nearest Neighbor Queries for Continuously Moving Points with Updates , 2003, VLDB.

[38]  Yunjun Gao,et al.  Processing Mutual Nearest Neighbor Queries for Moving Object Trajectories , 2008, The Ninth International Conference on Mobile Data Management (mdm 2008).

[39]  Amit P. Sheth,et al.  Semantic (Web) Technology In Action: Ontology Driven Information Systems for Search, Integration and Analysis , 2003, IEEE Data Eng. Bull..

[40]  Christian S. Jensen,et al.  Discovery of convoys in trajectory databases , 2008, Proc. VLDB Endow..

[41]  Keun Ho Ryu,et al.  Indexing for Efficient Managing Current and Past Trajectory of Moving Object , 2004, APWeb.

[42]  David Harel,et al.  Clustering spatial data using random walks , 2001, KDD '01.

[43]  M. R. Brito,et al.  Connectivity of the mutual k-nearest-neighbor graph in clustering and outlier detection , 1997 .

[44]  Jianwen Su,et al.  Universal trajectory queries for moving object databases , 2004, IEEE International Conference on Mobile Data Management, 2004. Proceedings. 2004.

[45]  Jae-Gil Lee,et al.  Trajectory clustering: a partition-and-group framework , 2007, SIGMOD '07.

[46]  Yufei Tao,et al.  Time-parameterized queries in spatio-temporal databases , 2002, SIGMOD '02.

[47]  Yufei Tao,et al.  MV3R-Tree: A Spatio-Temporal Access Method for Timestamp and Interval Queries , 2001, VLDB.

[48]  Yannis Manolopoulos,et al.  Fast Nearest-Neighbor Query Processing in Moving-Object Databases , 2003, GeoInformatica.

[49]  Timos K. Sellis,et al.  Spatio-temporal indexing for large multimedia applications , 1996, Proceedings of the Third IEEE International Conference on Multimedia Computing and Systems.

[50]  Jae-Gil Lee,et al.  TraClass: trajectory classification using hierarchical region-based and trajectory-based clustering , 2008, Proc. VLDB Endow..

[51]  Chris H. Q. Ding,et al.  K-nearest-neighbor consistency in data clustering: incorporating local information into global optimization , 2004, SAC '04.

[52]  Nikos Pelekis,et al.  Algorithms for Nearest Neighbor Search on Moving Object Trajectories , 2007, GeoInformatica.

[53]  Joachim Gudmundsson,et al.  Computing longest duration flocks in trajectory data , 2006, GIS '06.

[54]  Adnan Yazici,et al.  Modeling and querying fuzzy spatiotemporal databases , 2008, Inf. Sci..

[55]  Marios Hadjieleftheriou,et al.  Time relaxed spatiotemporal trajectory joins , 2005, GIS '05.

[56]  Raymond Chi-Wing Wong,et al.  On Efficient Spatial Matching , 2007, VLDB.

[57]  Yannis Theodoridis,et al.  Index-based Most Similar Trajectory Search , 2007, 2007 IEEE 23rd International Conference on Data Engineering.

[58]  Yunjun Gao,et al.  Efficient k-Nearest-Neighbor Search Algorithms for Historical Moving Object Trajectories , 2007, Journal of Computer Science and Technology.

[59]  Yunjun Gao,et al.  Algorithms for constrained k-nearest neighbor queries over moving object trajectories , 2010, GeoInformatica.