Mixed-Drove Spatiotemporal Co-Occurrence Pattern Mining

Mixed-drove spatio-temporal co-occurrence patterns (MDCOPs) represent subsets of two or more different object-types whose instances are often located in spatial and temporal proximity. Discovering MDCOPs is an important problem with many applications such as identifying tactics in battlefields, games, and predator-prey interactions. However, mining MDCOPs is computationally very expensive because the interest measures are computationally complex, datasets are larger due to the archival history, and the set of candidate patterns is exponential in the number of object-types. We propose a monotonic composite interest measure for discovering MDCOPs and novel MDCOP mining algorithms. Analytical results show that the proposed algorithms are correct and complete. Experimental results also show that the proposed methods are computationally more efficient than naive alternatives.

[1]  Shashi Shekhar,et al.  A join-less approach for co-location pattern mining: a summary of results , 2005, Fifth IEEE International Conference on Data Mining (ICDM'05).

[2]  Cédric du Mouza,et al.  Mobility Patterns , 2005, STDBM.

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

[4]  P. Diggle,et al.  Spatiotemporal prediction for log‐Gaussian Cox processes , 2001 .

[5]  Timos K. Sellis,et al.  Spatio-temporal Databases in the Years Ahead , 2003, Spatio-Temporal Databases: The CHOROCHRONOS Approach.

[6]  Panos Kalnis,et al.  On Discovering Moving Clusters in Spatio-temporal Data , 2005, SSTD.

[7]  Brian D. Ripley,et al.  Spatial Statistics: Ripley/Spatial Statistics , 2005 .

[8]  Zhe Jiang,et al.  Spatial Statistics , 2013 .

[9]  Timothy C. Coburn,et al.  Hierarchical Modeling and Analysis for Spatial Data , 2007 .

[10]  Bettina Speckmann,et al.  Efficient detection of motion patterns in spatio-temporal data sets , 2004, GIS '04.

[11]  George Kollios,et al.  Complex Spatio-Temporal Pattern Queries , 2005, VLDB.

[12]  Chris Chatfield,et al.  Statistical Methods for Spatial Data Analysis , 2004 .

[13]  Yan Huang,et al.  Discovering Spatial Co-location Patterns: A Summary of Results , 2001, SSTD.

[14]  Xin Zhang,et al.  Fast mining of spatial collocations , 2004, KDD.

[15]  William W. S. Wei,et al.  Time series analysis - univariate and multivariate methods , 1989 .

[16]  Hui Xiong,et al.  Discovering colocation patterns from spatial data sets: a general approach , 2004, IEEE Transactions on Knowledge and Data Engineering.

[17]  Shashi Shekhar,et al.  A partial join approach for mining co-location patterns , 2004, GIS '04.

[18]  C. Granger.  Time Series Analysis, Cointegration, and Applications , 2003 .

[19]  Mike Rees,et al.  5. Statistics for Spatial Data , 1993 .

[20]  Sw. Banerjee,et al.  Hierarchical Modeling and Analysis for Spatial Data , 2003 .

[21]  Petteri Nurmi,et al.  Moving Object Databases , 2008, Encyclopedia of GIS.

[22]  Shashi Shekhar,et al.  A Joinless Approach for Mining Spatial Colocation Patterns , 2006, IEEE Transactions on Knowledge and Data Engineering.

[23]  Patrick Laube,et al.  Analyzing Relative Motion within Groups of Trackable Moving Point Objects , 2002, GIScience.

[24]  Srinivasan Parthasarathy,et al.  A generalized framework for mining spatio-temporal patterns in scientific data , 2005, KDD '05.

[25]  Rakesh Agarwal,et al.  Fast Algorithms for Mining Association Rules , 1994, VLDB 1994.

[26]  Shashi Shekhar,et al.  Mixed-Drove Spatio-Temporal Co-occurrence Pattern Mining : A Summary of Results , 2006 .

[27]  S. Shekhar,et al.  Discovering Co-location Patterns from Spatial Datasets : A General Approach , 2004 .

[28]  Mong-Li Lee,et al.  A framework for mining topological patterns in spatio-temporal databases , 2005, CIKM '05.

[29]  Hsinchun Chen,et al.  Spatial-Temporal Cross-Correlation Analysis: A New Measure and a Case Study in Infectious Disease Informatics , 2006, ISI.

[30]  Nectaria Tryfona,et al.  Spatio-Temporal Databases: The CHOROCHRONOS Approach , 2003 .

[31]  Robert Haining,et al.  Statistics for spatial data: by Noel Cressie, 1991, John Wiley & Sons, New York, 900 p., ISBN 0-471-84336-9, US $89.95 , 1993 .

[32]  Nikos Mamoulis,et al.  Discovery of Collocation Episodes in Spatiotemporal Data , 2006, Sixth International Conference on Data Mining (ICDM'06).

[33]  Marc J. van Kreveld,et al.  Finding REMO - Detecting Relative Motion Patterns in Geospatial Lifelines , 2004, SDH.