Abstract
The spatial object fusion problem occurred in geographic information system is also met in spatial data warehouses, and it plays an important role in the spatial data preprocessing. A novel, equity-based and cell-based spatial object fusion method in spatial data warehouses, which only uses locations of objects and few computes distance among objects, is proposed and its efficiency and effectiveness are measured in terms of Recall and Precision in this paper. Especially, this method is very suitable for the cases, whose targets can be abstracted into point objects, such as the study about representative plants, animals and landscapes living in special environment. Our work extends the research about this field.
Supported by the National Natural Science Foundation of China (No . 60463004).
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References
Samal, A., Seth, S., Cueto, K.: A feature based approach to conflation of geospatial sources. International Journal of Geographical Information Science 18(00), 1–31 (2004)
Beeri, C., Kanza, Y., Safra, E., Sagiv, Y.: Object Fusion in Geographic Information Systems. In: Proceedings of the 30th VLDB Conference, Toronto, Canada, pp. 816–827 (2004)
Fonseca, T.F., Egenhofer, J.M., Agouris, P.: Using Ontologies For Integrated Geographic Information Systems. Transactions in GIS 6(3) (2002)
Fonseca, T.F., Egenhofer, J.M.: Ontologydriven Geographic Information Systems. In: Proceedings of the 7th ACM International Symposium on Advances in Geographic Information Systems, Kansas City (Missouri, US), pp. 14–19 (1999)
Uitermark, H., Oosterom, V.P., Mars, N., Molenaar, M.: Ontology-Based Geographic Data Set Integration. In: Proceedings of Workshop on Spatio-Temporal Database Management, Edinburgh (Scotland), pp. 60–79 (1999)
Minami, M.: Using ArcMap. Environmental Systems Research Institute, Inc. (2000)
Agrawal, R., Gehrke, J., Gunopulos, D., Raghavan, P.: Automatic Subspace Clustering Of High Dimensional Data For Data Mining Applications. In: Proceedings of the ACM SIGMOD Conference on Management of Data, Seattle, WA, pp. 94–105 (1998)
Bruns, T., Egenhofer, M.: Similarity Of Spatial Scenes. In: Proceedings of the 7th International Symposium on Spatial Data Handling, Delft (Netherlands), pp. 31–42 (1996)
Wang, W., Yang, J., Muntz, R.: STING: A Statistical Information Grid Approach to Spatial Data Mining. In: Proceedings of the 23rd VLDB Conference, Athens, Greece, pp. 186–195 (1997)
Papakonstantinou, Y., Abiteboul, S., Garcia-Molina, H.: Object Fusion in Mediator Systems. In: Proceedings of the 22nd VLDB Conference, Mumbai (Bombay), India, pp. 413–424 (1996)
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Li, H., Wang, L. (2005). An Equity-Based and Cell-Based Spatial Object Fusion Method. In: Grumbach, S., Sui, L., Vianu, V. (eds) Advances in Computer Science – ASIAN 2005. Data Management on the Web. ASIAN 2005. Lecture Notes in Computer Science, vol 3818. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11596370_23
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DOI: https://doi.org/10.1007/11596370_23
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