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SPATIAL DATABASES TEXTBOOK

Title : Spatial Databases: A Tour Authors: Shashi Shekhar and Sanjay Chawla Publisher: Prentice Hall, 2003 (ISBN 013-017480-7) Status: Published on June 15th, 2002. For more detail, please click here

RESEARCH PAPERS

Spatial Data Mining

Spatial Databases

Spatio-Temporal Data Mining

Spatio-Temporal Databases

Real Time Search

Learning and Discovery in Databases

Spatial Data Mining

• General Spatial Data Mining
  • S. Shekhar, P. Zhang, Y. Huang, R. Vatsavai, Trend in Spatail Data Mining, as a chapter to appear in Data Mining: Next Generation Challenges and Future Directions, H. Kargupta, A. Joshi, K. Sivakumar, and Y. Yesha(eds.), AAAI/MIT Press, 2003, (pdf, PS)
  • S. Shekhar, R. Vatsavai, Techniques for Mining Geospatial Databases, as Chapter 22 in Handbook of Data Mining, Nong Ye (Eds.), LEA Publishers, NJ, 2003.
  • S. Shekhar, Y. Huang, W. Wu, C.T. Lu, What's Spatial about Spatial Data Mining: Three Case Studies , as Chapter of Book: Data Mining for Scientific and Engineering Applications. V. Kumar, R. Grossman, C. Kamath, R. Namburu (eds.), Kluwer Academic Pub., 2001, ISBN 1-4020-0033-2. (PS, PDF)
  • S. Chawla, S. Shekhar, W. Wu, U. Ozesmi, Modeling Spatial Dependencies for Mining Geospatial Data: An Introduction , as Chapter of Geographic Data Mining and Knowledge Discovery. Harvey J. Miller and Jiawei Han (eds.) Taylor and Francis, 2001, ISBN 0-415-23369-0. . (PS, PDF)
• Data Mining on Earth Science Data
  • Zhang, P., Steinbach, M., Kumar, V., Shekhar, S., Tan, P., Klooster, S., and Potter, C, Discovery of Patterns of Earth Science Data Using Data Mining, as a chapter to appear in Next Generation of Data Mining Applications, Mehmed M. Kantardzic and Jozef Zurada (editors), IEEE Press, 2004 (pdf )
• Spatial Outlier Detection
  • S. Shekhar, C.T. Lu, P. Zhang, A Unified Approach to Spatial Outliers Detection, to appear in Geoinformatica, 7(2), June, 2003. (PS, PDF)
  • S. Shekhar, C.T. Lu, P. Zhang Detecting Graph-based Spatial Outliers: Algorithms and Applications, Proceedings of the Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2001, San Francisco, CA, 2001. (PS, PDF). An extended version appeared in International Journal of Intelligent Data Analysis, 6(5), IOS press. . (PS, PDF)
• Spatial Location Prediction
  • B. M. Kazar, S. Shekhar, D. J. Lilja, D. Shires, J. Rogers, M. Celik, A Parallel Formulation of the Spatial Auto-Regression Model, to appear in the International Conference on Geographic Information GIS PLANET, May 2005, Lisbon, Portugal.
  • S. Shekhar, B. M. Kazar, D. J. Lilja, Scalable Parallel Approximate Formulations of Multi-Dimensional Spatial Auto-Regression Models for Spatial Data Mining, to appear as summary paper in the 24th Army Science Conference, November 2004, Orlando FL, USA. (PDF)
  • B. M. Kazar, S. Shekhar, D. J. Lilja, R. R. Vatsavai, R. K. Pace, Comparing Exact and Approximate Spatial Auto-Regression Model Solutions for Spatial Data Analysis, to appear in the Proc. of Third International Conference on Geographic Information Science (GIScience2004), Maryland, USA, October 2004. (PDF)
  • B. M. Kazar, S. Shekhar, D. J. Lilja, D. Boley, A Parallel Formulation of the Spatial Auto-Regression Model for Mining Large Geo-Spatial Datasets, to appear in Proc. of 2004 SIAM International Conf. on Data Mining Workshop on High Performance and Distributed Mining (HPDM2004), Florida, USA, April 2004. (PS, PDF)
  • S. Shekhar, P. Schrater, R. Vatsavai, W. Wu, and S. Chawla, Spatial Contextual Classification and Prediction Models for Mining Geospatial Data , to appear in IEEE Transactions on Multimedia (special issue on Multimedia Dataabses) , 2002. (PS, PDF)
  • S. Chawla, S. Shekhar, W. Wu, U. Ozesmi, Modeling Spatial Dependencies for Mining Geospatial Data , Proc. of the 1st SIAM International Conference on Data Mining Chicago, IL, 2001. (PS, PDF)
  • S. Chawla, S. Shekhar, W. Wu and U. Ozesmi, Extending Data Mining for Spatial Applications: A Case Study in Predicting Nest Locations, Proc. Int. Confi. on 2000 ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery (DMKD 2000), Dallas, TX, May 14, 2000.. (PS, PDF)
  • S. Chawla, S. Shekhar, W. Wu, Predicting Locations Using Map Similarity (PLUMS): A Framework for Spatial Data Mining , Proc. of the 6th International Conference on Knowledge Discovery and Data Mining, Boston, MA, 2000. (PS, PDF) Talk (Power Point)
• Co-location Mining
  • Mete Celik, James M. Kang, Shashi Shekhar, Zonal Co-location Pattern Discovery with Dynamic Parameters, In Proc. of 7th IEEE Int’ l Conf. on Data Mining (ICDM), Omaha, Nebraska, 2007. (PDF)
  • Jin Soung Yoo and Shashi Shekhar, A Join-less Approach for Mining Spatial Co-location Patterns, the IEEE Transactions on Knowledge and Data Engineering (TKDE), Vol.18, No.10, 2006. PDF
  • Jin Soung Yoo, Shashi Shekhar and Mete Celik, A Join-less Approach for Co-location Pattern Mining: A Summary of Results, in Proc. of the IEEE International Conference on Data Mining(ICDM), Houston, USA, 2005 (Short: PS, PDF), (Full: PS, PDF)
  • Jin Soung Yoo and Shashi Shekhar, A Partial Join Approach for Mining Co-location Patterns, in Proc. of the 12th ACM International Symposium on Advances in Geographic Information Systems(ACM-GIS), Washington D.C., USA, 2004 (PS, PDF)
  • Hui Xiong, Shashi Shekhar, Yan Huang, Vipin Kumar, Xiaobin Ma, Jin Soung Yoo, A Framework for Discovering Co-location Patterns in Data Sets with Extended Spatial Objects, in Proc. of SIAM International Conf. on Data Mining (SDM), Florida, USA, 2004. (PDF)
  • Yan Huang, Shashi Shekhar, and Hui Xiong, Discovering Co-location Patterns from Spatial Datasets: A General Approach, IEEE Transactions on Knowledge and Data Engineering (TKDE), 16(12), pp. 1472-1485, December 2004, (PS, PDF)
    
  • Yan Huang, Hui Xiong, Shashi Shekhar,and Jian Pei, Mining Confident Co-location Rules without A Support Threshold, to appear in Proc. of 18th ACM Symposium on Applied Computing (ACM SAC), Melbourne, FL, March 2003 (PS, PDF)
  • S. Shekhar and Y. Huang, Discovering Spatial Co-location Patterns: A Summary of Results , Proc. of 7th International Symposium on Spatial and Temporal Databases(SSTD01), L.A., CA, July 2001. (PS, PDF)
• Hot Spot Discovery - Crime Analysis
  • Mete Celik, Shashi Shekhar, Betsy George, James P. Rogers, James A. Shine, Discovering and Quantifying Mean Streets: A Summary of Results, University of Minnesota, Department of Computer Science, Technical Report, no. 07-025, 2007. (Link, PDF )

 

SPATIAL DATABASES

• Survey Paper
  • V. Gandhi, J. M. Kang, S. Shekhar, Spatial Databases, Technical Report TR07-020, Dept. of Compter Sci., U. of Minnesota, 2007. (Updated from Shekhar et al. TKDE '99)
  • S. Shekhar, S. Chawla, S. Ravada, A. Fetterer, X. Liu and C.T. Liu, Spatial Databases: Accomplishments and Research Needs , IEEE Transactions on Knowledge and Data Engineering, Jan.-Feb. 1999. .
• MapCube
  • S. Shekhar, C.T. Lu, P. Zhang, and R. Liu, Data Mining for Selective Visualization of Large Spatial Datasets 14th IEEE International Conference On Tools with Artificial Intelligence, 2002 . (PS, PDF)
  • S. Shekhar, C.T. Lu, X. Tan, S. Chawla, Map Cube: A Visualization Tool for Spatial Data Warehouses, as Chapter of Geographic Data Mining and Knowledge Discovery. Harvey J. Miller and Jiawei Han (eds.), Taylor and Francis, 2001, ISBN 0-415-23369-0. . (PS, PDF)
  • S. Shekhar, C.T. Lu, X. Tan, S. Chawla, Map Cube: A Visualization Tool for Spatial Data Warehouses - A Summary of Result, Proceedings of NSF workshop on Data Mining in GIS, March, 1999 . (PS, PDF)
  • S. Shekhar, C.T. Lu, R. Liu, and C. Zhou, CubeView: A System for Traffic Data Visualization, the Proceedings of the Fifth IEEE International Conference on Intelligent Transportation Systems , 2002. PDF
• Query Processing in Spatial Time Series Datasets
  • P. Zhang, S. Shekhar, Yan Huang, and V. Kumar, Spatial Cone Tree: An Index Structure for Correlation-based Similarity Queries on Spatial Time Series, in the Proc. of Int'l Workshop on Next Generation Geospatial Information, Boston, MA, Oct. 2003
  • P. Zhang, Y. Huang, S. Shekhar, and V. Kumar, Exploiting Spatial Autocorrelation to Efficiently Process Correlation-Based Similarity Queries, to appear in the Proceedings of the 8th Symp. on Spatial and Temporal Databases , July 25-27, 2003, Santorini island, Greece. , (PS, PDF)
  • P. Zhang, Y. Huang, S. Shekhar, and V. Kumar, Correlation Analysis of Spatial Time Series Datasets: A Filter-and-Refine Approach, to appear in the Proceedings of Seventh Pacific-Asia Knowledge Discovery and Data Mining Apr. 30-May 2, 2003, Seoul, Korea. (PS, PDF)
• Map Compression
  • Shashi Shekhar, Yan Huang, Judy Djugash, Changqing Zhou, Vector Map Compression: A Clustering Approach. ACMGIS 2002, November 8-9, 2002, McLean, Virginia, USA. . (PS, PDF)
  • Shashi Shekhar, Yan Huang, and Judy Djugash Dictionary Design Algorithms for Vector Map Compression In Proc. of IEEE Data Compression Conference (DCC) , Snowbird, UT, April 2002 (PS, PDF)
• Directional Query Processing
  • X. Liu, S. Shekhar, S. Chawla, Processing Object-orientation-based Direction Queries , IEEE Transaction of Knowledge and Data Engineering, 15(2), 2003. A summary of results was accepted in ACMGIS 2000.
  • X. Liu, S. Shekhar, S. Chawla, Consistency Checking for Euclidean Spatial Constraints: A Dimension Graph Approach , Technical Report TR00-039, Dept. of Compter Sci., U. of Minnesota, A summary of results was accepted in the International Conference of Tools for AI(ICTAI2000) .
  • S. Shekhar, X. Liu, S. Chawla, Equivalence Classes of Direction Objects and Applications , Technical Report TR99-027, University of Minnesota, Minneapolis, MN. Will submit to IJGIS .
  • S. Shekhar, X. Liu, S. Chawla, An Object Model of Direction and Its Implications, GeoInformatica 3:4, 357-379 (1999), Kluwer Academic Publishers; A summary of results was among 5 best papers in Sixth International Symposium on Advances in Geographic Information System(1998).
• Spatial Join Index
  • S. Shekhar, C.T. Lu, S. Chawla, S. Ravada, Efficient Join Index Based Join Processing; A Clustering Approach, IEEE Transactions on Knowledge and Data Engineering, 15(1), 2003. (PS, PDF)
  • S. Ravada, S. Shekhar, C.T. Lu Optimizing Join Index Based Spatial-Join Processing: A Graph Partitioning Approach, 17th IEEE Symposium on Reliable Distributed Systems, West Lafayette, Indiana, October 1998 .
• Spatial Modeling
  • S. Shekhar, R. Vatsavai, S.Chawla, T. Burk Spatial Pictorgram Enhanced Conceptual Data Models and Their Translation to Logical Data Models. Integrated Spatial Databases: Digital Images and GIS. Lecture Notes in Computer Science, Vol. 1737, Springer Verlag, Dec. 1999. Editors: P. Agouris and A. Stefanidis .
  • S. Shekhar, M.Coyle, B. Goyal, D. R. Liu, and S. S. Sarkar, Experiences with Data Models in Geographic Information Systems, Communications of the ACM , Vol. 40, No. 4, April 1997. (Tech. Report TR95-10, Univ. of Minnesota, Computer Sc. Dept.).
• Declustering Problem
  • S. Shekhar, S. Ravada, V. Kumar, D. Chubb, and G. Turner, Declustering and Load-Balancing Methods for Parallelizing Spatial Databases , to appear in IEEE Transactions on Knowledge and Data Engineering .
  • S. Shekhar and D. R. Liu, Partitioning Similarity Graphs: A Framework for Declustering Problems, Information Systems: An Intl. Jr., Pergamon Press, Vol. 21, No. 4, Sept. 1996. Also CSci TR 94-18.
• Routing, Planning, and Spatial Networks
  • Sangho Kim, Shashi Shekhar, and Manki Min, Contraflow Transportation Network Reconfiguration for Evacuation Route Planning, IEEE Transactions on Knowledge and Data Engineering, 20(8), 2008. (PDF)
  • Sangho Kim, Betsy George, and Shashi Shekhar. Evacuation Route Planning: Scalable Heuristics. ACMGIS 07, Seattle, WA, 2007. (PDF)
  • Qingsong Lu, Betsy George, and Shashi Shekhar, Evacuation Route Planning : A Case Study in Semantic Computing, International Journal of Semantic Computing Volume(1), Number 2, June 2007. (PDF)
  • Qingsong Lu, Betsy George, and Shashi Shekhar, Capacity Constrained Routing Algorithms for Evacuation Planning: A Summary of Results, Advances in Spatial and Temporal Databases, Proceeding of 9th International Symposium on Spatial and Temporal Databases (SSTD'05), Angra dos Reis, Brazil, August 22-24, 2005. (PDF)
  • Sangho Kim and Shashi Shekhar. Contraflow Network Reconfiguration for Evacuation Planning: A Summary of Results. ACMGIS 05, Bremen, Germany, 2005. (PDF)
  • Jin Soung Yoo and Shashi Shekhar, In-Route Nearest Neighbor Queries, in Proc. of Geoinformatica, Volume 9, Issue 2, June 2005(PDF)
  • Shashi Shekhar and Jin Soung Yoo, Processing In-Route Nearest Neighbor Queries: A Comparison of Alternative Approaches, in Prof. of the 11th ACM International Symposium on Advances in Geographic Information Systems (ACM-GIS), New Orleans, USA, 2003(Best Paper Award)(PDF)
  • Qingsong Lu, Yan Huang, and Shashi Shekhar, Evacuation Planning: A Capacity Constrained Routing Approach, in Proceeding of the First NSF/NIJ Symposium on Intelligence and Security Informatics (ISI 2003), (PS, PDF)
    
  • S. Shekhar, A. Fetterer, and B. Goyal, Materialization Trade-Offs in Hierarchical Shortest Path Algorithms , Proc. Intl. Symp. on Large Spatial Databases, Springer Verlag (Lecture Notes in Computer Science), (1997).
  • S. Shekhar, M. Coyle, and A. Kohli, Path Computation Algorithms for Advanced Traveller Information System , Proc. Intl. Conf. on Date Engineering , (IEEE Computer Society), (1993).
• Spatial Access Method
  • S. Shekhar and D. R. Liu, CCAM: A Connectivity-Clustered Access Method for Networks and Network Computations, IEEE Trans. on Knowledge and Data Engineering, Vol. 9, No. 1, Jan. 1997. Csci TR 93-78.
• GIS anf High Performance GIS
  • S. Shekhar, S. Ravada, V. Kumar, D. Chubb, and G. Turner, Parallelizing a GIS on a Shared-Address Space Architecture , IEEE Computer, December, 1996.
  • S. Shekhar, D. R. Liu, and A. Fetterer, Genesis: An Approach to Data Dissemination in Advanced Traveler Information Systems , Bulletin of the Technical Committee on Data Engineering: Special Issue on Data Dissemination, September 1996, Vol 19, No. 3.
  • S. Shekhar, A. Fetterer, Path Computation in Advanced Traveler Information Systems, Proc. Intelligent Transportation Systems (1996)
  • A. A. El Haddi, S. Shekhar, S. Carroll, Mirror-Image Round Robin Spatial Data Partitioning: A Case Study With Parallel SEUS, Proc. Intl. Conf. on Integrating Gegraphic Info. Systems with Environmental Modeling, National Center for Geographic Info. and Analysis (NCGIA), Jan. 1996 . remote or local copy
  • S. Shekhar, S. Ravada, G. Turner, D. Chubb, and V. Kumar, Load Balancing in High Performance GIS: Partitioning Polygonal Maps, Proc. Intl. Symp. on Large Spatial Databases, Springer Verlag (Lecture Notes in Computer Science), (1995). (Selection 1 in 3).
  • S. Shekhar and D. R. Liu, Genesis and Advanced Traveller Information Systems (ATIS): Killer Applications for Mobile Computing?, Proc. Workshop on Mobile and Wireless Information Systems, National Science Foundation, (Oct. 1994).
  • S. Shekhar and M. Coyle, Evaluation of Disk Allocation Method for Spatial Queries on Grid Files, Journal of Computer and Software Engineering, Accepted for the special issue on Parallel Algorithms and Architectures.
• Map and GPS Accuracy
  • P. Cheng, M. Donath, X. Ma, S. Shekhar, and Kenneth Buckeye Evaluation of Digital Maps for Road User Charging Applications User Charge Systems , In submission to Journal of Transportation Research Board (TRB), 2005
  • P. Cheng, X. Ma, M. Donath, and S. Shekhar, Evaluation of National Differential Global Positioning System (ND GPS) for Accessing Road User Charge Systems , Journal of Transportation Research Board (TRB), 2004
  • S. Shekhar, X. Ma, H. Xiong, M. Donath, P. Cheng, and W. Wu Digital Road Map Evaluation : a Buffer-based Approach The joint meeting of The Fifteenth Annual Conference of The International Environmetrics Society and The Sixth International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences, 2004.

 

SPATIO-TEMPORAL DATA MINING

• Spatio-Temporal Co-occurrence Pattern Mining
  • Mete Celik, Shashi Shekhar, James Rogers, James Shine, Mining Mixed-drove Spatio-temporal Co-occurrence Patterns: A Summary of Results, Accepted to the TKDE 2008(PDF).
  • Mete Celik, Shashi Shekhar, James Rogers, James Shine, and James M. Kang, Mining At Most Top-K% Mixed-drove Spatio-temporal Co-occurrence Patterns: A Summary of Results, In Proc. of the Workshop on Spatio-Temporal Data Mining (In conjunction with IEEE ICDE 2007), Istanbul, Turkey, 2007.
  • Mete Celik, Shashi Shekhar, James Rogers, James Shine, and Jin S. Yoo, Mining Mixed-drove Spatio-temporal Co-occurrence Patterns: A Summary of Results, In Proc. of 6th IEEE Int’ l Conf. on Data Mining (ICDM), Hong Kong, 2006. (PDF).
  • Mete Celik, Shashi Shekhar, James Rogers, and James Shine, Sustained Emerging Spatio-temporal Co-occurrence Pattern Mining: A Summary of Results, In Proc. of IEEE Int’ l Conf. on Tools on Artificial Intelligence (ICTAI) Washington, D.C., 2006.
• Time-Profiled Association Mining
  • Jin Soung Yoo, Shashi Shekhar, Sangho Kim and Mete Celik, Discovery of Co-evolving Spatial Event Sets, In Proceedings of the SIAM International Conference on Data Mining (SDM), Maryland, USA, 2006. PDF
  • Jin Soung Yoo, Pusheng Zhang and Shashi Shekhar, Mining Time-Profiled Associations: An Extended Abstract, in Proc. of International Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Hanoi, Vietnam, 2005 (PS, PDF)

 

SPATIO-TEMPORAL DATABASES

• Spatio-Temporal Graph Databases
  • Betsy George, Sangho Kim, Shashi Shekhar, Spatio-temporal Network Databases and Routing Algotihms: A Summary of Results, Proceedings of International Symposium on Spatial and Temporal Databases (SSTD`07), Boston, July, 2007. (PDF)
  • Betsy George, Shashi Shekhar, Time Aggregated Graphs for Modeling Spatio-temporal Network, Journal on Semantics of Data (Editors: J.F. Roddick, S. Spaccapietra), Vol XI, December, 2007. (PDF)
  • Betsy George, Shashi Shekhar, Modeling Spatio-temporal Network Computations: A Summary of Results, Proceedings of the Second International Conference on GeoSpatial Semantics (GeoS 2007), Mexico City, Mexico, November, 2007. (PDF)
  • Betsy George, James Kang, Shashi Shekhar, STSG: A Data Model for Representation and Knowledge Discovery in Sensor Data, Proceedings of Workshop on Knowledge from Sensor Data (SensorKDD `07) at ACM-SIGKDD, San Jose, CA, August, 2007. ( PDF)

REAL TIME SEARCH

• S. Shekhar and B. Hamidzadeh, Specification and Analysis of Real Time Problem Solvers, Trans. on Software Engineering, IEEE, (Nov. 1993). also Csci TR 93-08.
• S. Shekhar and B. Hamidzadeh, SARTS: A Dependable Real Time Search Algorithm, Accepted (with revisions) for Trans. on Knowledge and Data Engineering, IEEE, (). also Csci TR 93-23.
• S. Shekhar and B. Hamidzadeh, DynoraII: A Real-Time Planning Algorithm, Intl. Jr. on Artificial Intelligence Tools (Special issue on real-time AI) 2(1)pp. 93-115 World Scientific Publishers, (1993).
• S. Shekhar and B. Hamidzadeh, Evaluation of Real-Time Problem Solvers in Dynamic Enviroments, Intl. Jr. on Artificial Intelligence Tools 2(4)pp. 459-484 World Scientific Publishers, (1993). (Selected paper from IEEE Conf. on Tools for AI 1992).

LEARNING AND DISCOVERY IN DATABASES

• S. Shekhar and B. Hamidzadeh, Learning Transformation Rules for Semantic Query Optimization: A Data-Driven Approach, Trans. Knowledge and Data Eng. (Spl. Issue on Discovery in Databases), IEEE, (Oct. 1993). also Csci TR 93-07.
• S. Shekhar and B. Hamidzadeh, Learning Transformation Rules for Semantic Query Optimization: A Data-Driven Approach, Trans. Knowledge and Data Eng. (Spl. Issue on Discovery in Databases), IEEE, (Oct. 1993). also Csci TR 93-07.
• V. Kumar, A. Balakrishnan, and S. Shekhar, A Scalable Parallel Formulation of Backpropagation Algorithm for Hypercubes and Related Architectures, Trans. on Parallel and Distr. Systems, IEEE, (Oct. 1994). also Csci TR 92-54.
• S. Shekhar and A. Balakrishnan, Generalization by Neural Networks , Trans. on Knowledge and Data Eng., IEEE, (April 1992).