Open Access Open Access  Restricted Access Subscription or Fee Access

A Study of Mining for Spatially Co-Located Moving Objects

G. Manikandan, S. Srinivasan


In this paper, we have presented a novel approaches for effectively mining of spatially co-located moving objects from the spatial databases. We propose a novel technique for co-location pattern mining which materializes spatial neighbor relationships with no loss of co-location instances and reduces the computational cost with the aid of the Prim's Algorithm. The spatially co-location mining technique is efficient since it generates and filters the candidate instances. Subsequently, the neighborhood relationships are carried out by the designed neighborhood and the node membership functions which satisfy the minimum conditional threshold. This paper has been inspired by the Join-less approach for mining spatial co-location patterns. We use a spatial database that contains the moving objects and its corresponding spatial location for spatial co-location pattern mining to mine spatially co-located moving objects.


Spatial Data Mining, Co-Location, Prim‟s Algorithm, Moving Objects

Full Text:



Vaibhav Kant Singh, Vijay Shah, Yogendra Kumar Jain, Anupam Shukla, A.S. Thoke, Vinay Kumar Singh, Chhaya Dule and Vivek Parganiha, "Proposing an Efficient Method for Frequent Pattern Mining", In Proceedings of the World Academy of Science, Engineering and Technology, Vol.61, pp. 384-390, 2008.

Bin Li and Dennis Shasha, "Free Parallel Data Mining", ACM SIGMOD Record, Vol.27, No.2, pp.541-543, June 1998.

Sathiyamoorthi and Murali Bhaskaran, "Data Mining for Intelligent Enterprise Resource Planning System", International Journal of Recent Trends in Engineering, Vol. 2, No. 3, pp.1-5, November 2009.

W. Frawley, G. Piatetsky-Shapiro, and C. Matheus, “Knowledge Discovery in Databases: An Overview”, AI Magazine, pp. 213-228, 1992.

J. Han and M. Kamber, “Data Mining: Concepts and Techniques,” Morgan Kaufman, 2001.

Huan Liu and Lei Yu, “Toward Integrating Feature Selection Algorithms for Classification and Clustering”, IEEE Transactions on Knowledge and Data Engineering, Vol. 17, No. 4, April 2005.

J. Han and Y. Fu, “Attribute-Oriented Induction in Data Mining,” Advances in Knowledge Discovery and Data Mining, U.M. Fayyad, G. Piatetsky-Shapiro, P. Smyth, and R. Uthurusamy, eds., pp. 399- 421, AAAI Press/The MIT Press, Menlo Park, CA, 1996.

Klaus Julisch, "Data Mining for Intrusion Detection -A Critical Review", In Proceedings of IBM Research on application of Data Mining in Computer security, D. Barbara and S. Jajodia, eds., Chapter 1 , Kluwer Academic Publisher, 2002.

Hewen Tang, Wei Fang and Yongsheng Cao, "A Simple Method of Classification with VCL Components", In Proceedings of the 21st international CODATA Conference, Kyiv, Ukraine, October, 2008.

You Wan, Jiaogen Zhou, Fuling Bian, "CODEM: A Novel Spatial Co-location and De-location Patterns Mining Algorithm", in proceedings of the Fifth International Conference on Fuzzy Systems and Knowledge Discovery, Shandong, Vol: 2, pp: 576, 2008.

Yan Huang, Shashi Shekhar, Hui Xiong, "Discovering Co-location Patterns from Spatial Datasets: A General Approach", IEEE Transactions On Knowledge And Data Engineering, vol. 16, no. 12, pp 513-522, 2006.

“Co-location GIS Encyclopedia Article Draft” from “” by Wei Hu.

Yan Huang, Jian Pei, Hui Xiong, “Mining Co-location Patterns with rare events from Spatial Data Sets”, Geoinformatica, vol. 10, no.3, 2006.

J. Yoo, S. Shekhar, John Smith and Julius P. Kumquat, “A Partial Join Approach for Mining Co-location Patterns”, in Proceedings of 12th annual ACM international workshop on Geographic information systems, New York, 2004.

M. Kuramochi and G.Karypis, “Frequent Subgraph Discovery”, in Proceedings of IEEE International Conference on Data Mining, 2004.

Shekhar, S., and Huang, Y., “Discovering Spatial Co-location Patterns: A Summary of Results”, In Proceedings of the 7th International Symposium on Advances in Spatial and Temporal Databases, Springer-Verlag, London, pp. 236-256. 2001.

Lizhen Wang, Yuzhen Bao and Zhongyu Lu, "Efficient Discovery of Spatial Co-Location Patterns Using the iCPI-tree", The Open Information Systems Journal, vol. 3, pp. 69-80, 2009.

Al-Naymat, G., "Enumeration of maximal clique for mining spatial co-location patterns", in proceedings of the IEEE/ACS International Conference on Computer Systems and Applications, pp: 126, Doha, 2008.

Lizhen Wang, Yuzhen Bao, Lu, J., Yip, J., "A new join-less approach for co-location pattern mining", n proceedings of the 8th IEEE International Conference on Computer and Information Technology, Sydney, NSW, pp: 197, 2008.

Yue Jiang, Lizhen Wang, Ye Lu, Hongmei Chen, "Discovering both positive and negative co-location rules from spatial data sets", in proceedings of the 2nd International Conference on Software Engineering and Data Mining, Chengdu, pp: 398, 2010.

Yoo, J.S.; Shekhar, S.; "A Joinless Approach for Mining Spatial Colocation Patterns", IEEE Transactions on Knowledge and Data Engineering, Vol: 18, No:10, pp: 1323 - 1337, 2006.

Lizhen Wang, Lihua Zhou, Joan Lu and Jim Yip, "An order-clique-based approach for mining maximal co-locations", Information Sciences, Vol: 179, No: 19, pp: 3370-3382, 2009.

Shashi Shekhar, Pusheng Zhang, Yan Huang, and Ranga Raju Vatsavai, “Chapter 3 Trends in Spatial Data Mining”, Data Mining: Next Generation Challenges and Future Directions, Hillol Kargupta and Anupam Joshi(eds.,), AAAI/MIT Press, 2003.

Patrick Laube, Mark de Berg, and Marc van Kreveld, “Spatial Support and Spatial Confidence for Spatial Association Rules”, Headway in Spatial Data Handling, Lecture Notes in Geoinformation and Cartography, pp.575-593, 2008.

“Data mining” from “”.

Kapil Aggarwal, “Performance Optimization of Database Operations in Spatial Database Systems”, In Proceedings of ICCS International Conference, Delhi, December 2004.

Shashi Shekhar, Chang-Tien Lu and Pusheng Zhang, “A Unified Approach to Detecting Spatial Outliers”, Geoinformatica, Vol. 7, No. 2, pp.139–166, 2003.

Chang-Tien Lu, Dechang Chen and Yufeng Kou, “Detecting Spatial Outliers With Multiple Attributes”, In Proceedings of the 15th IEEE International Conference on Tools with Artificial Intelligence (ICTAI‟04), pp. 122–128, 2003.

Yukio Sadahiro, “Cluster Detection in Uncertain Point Distributions: A Comparison of Four Methods”, Computers, Environment and Urban Systems, Vol. 27, No.1, pp. 33–52, 2003.

Joachim Gudmundsson, Marc van Kreveld and Bettina Speckmann, “Efficient Detection of Patterns in 2D Trajectories of Moving Points”, GeoInformatica, Vol.11, No. 2, pp. 195–215, 2007.

Patrick Laube, Stephan Imfeld and Robert Weibel, “Discovering Relative Motion Patterns in Groups of Moving Point Objects”, International Journal of Geographical Information Science, Vol. 19, No. 6, pp. 639–668, 2005.

Feng Qian, Qinming He and Jiangfeng He, "Mining Spatial Co-location Patterns with Dynamic Neighborhood Constraint", Machine Learning and Knowledge Discovery in Databases, Lecture Notes in Computer Science, Vol: 5782, pp: 238-253, 2009.

You Wan, Jiaogen Zhou, "KNFCOM-T: a k-nearest features-based co-location pattern mining algorithm for large spatial data sets by using T-trees", International Journal of Business Intelligence and Data Mining, Vol. 3, No.4, pp. 375 - 389, 2008.

Chin Jui Chang and Shiahn Wern Shyue, “Spatial and Temporal Data Mining in Census of Population and Housing”, In Proceedings of the International Conference on Business And Information (BAI), January 12-14, Singapore, 2006.

N.A.C. Cressie, “Statistics for Spatial Data”. Wiley and Sons, ISBN: 0471843369, 1991.

Y. Chou, “Exploring Spatial Analysis in Geographic Information System”, Onward Press, ISBN: 1566901197, 1997.

V. Estivill-Castro and A. Murray, “Discovering Associations in Spatial Data - An Efficient Medoid Based Approach”, In Proceedings of the Second Pacific-Asia Conference on Knowledge Discovery and Data Mining, 1998.

V. Estivill-Castro and I. Lee, “Data Mining Techniques for Autonomous Exploration of Large Volumes of Geo-referenced Crime Data”, In Proceedings of the 6th International Conference on Geo-computation, 2001.

R. Agarwal and R. Srikant, “Fast Algorithms for Mining Association Rules”, In Proceedings of the 20th International Conference on Very Large Data Bases, 1994.

K. Koperski and J. Han, “Discovery of Spatial Association Rules in Geographic Information Databases”, In Proceedings of the 4th International Symposium on Spatial Databases, 1995.

Y. Morimoto, “Mining Frequent Neighboring Class Sets in Spatial Databases”, In Proceedings of ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2001.

S. Shekhar and Y. Huang, “Co-location Rules Mining: A Summary of Results”, In Proceedings of 7th International Symposium on Spatio-temporal Databases, 2001.

Martin Ester, Hans-Peter Kriegel, Jorg Sander, “Spatial Data Mining: A Database Approach”, in Proceedings of the Fifth International Symposium on Large Spatial Databases (SSD „97), Berlin, Germany, Lecture Notes in Computer Science, Springer, 1997.


  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.