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Determining Topological Relationship of Fuzzy Spatiotemporal Data in XML

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Modeling Fuzzy Spatiotemporal Data with XML

Part of the book series: Studies in Computational Intelligence ((SCI,volume 894))

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Abstract

How to determine topological relationship is one of the most important operations on fuzzy spatiotemporal data. The proposed strategies impose strict restrictions on structure and data types of fuzzy spatiotemporal data, and fall short in their abilities to handle fuzzy attributes extension and fuzzy time extension. To overcome these limitations, we propose strategies of transforming two general fuzzy spatiotemporal data trees into one binary fuzzy spatiotemporal data tree. In succession, an effective algorithm to match the desired twigs is proposed after extending the region coding scheme to compatible with fuzzy spatiotemporal data. Our approach adopts XML twig pattern technique to determine topological relationship continuously so that it can reduce unnecessary execution time of querying the desired nodes. More importantly, pointer array is used to eliminate unnecessary execution time of twig matching. Finally, the experimental results demonstrate the performance advantages of our approach.

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References

  • Al-Khalifa, S., Jagadish, H. V., Koudas, N., Patel, J. M., Srivastava, D., & Wu, Y. (2002). Structural joins: A primitive for efficient XML query pattern matching. In Proceedings of the 18th International Conference on Data Engineering (pp. 141–152). San Jose, CA: IEEE.

    Google Scholar 

  • Bao, L., Qin, X. L., Zhang, J., & Li, Q. Y. (2006). Reasoning the spatiotemporal relations between time evolving indeterminate regions. In Advances in Machine Learning and Cybernetics (pp. 448–458). Springer, Berlin, Heidelberg.

    Google Scholar 

  • Bennett, B., Cohn, A. G., Wolter, F., & Zakharyaschev, M. (2002). Multi-dimensional modal logic as a framework for spatio-temporal reasoning. Applied Intelligence, 17(3), 239–251.

    Article  Google Scholar 

  • Bruno, N., Koudas, N., & Srivastava, D. (2002). Holistic twig joins: optimal XML pattern matching. In Proceedings of the 2002 ACM SIGMOD International Conference on Management of Data (pp. 310–321). Madison, Wisconsin: ACM.

    Google Scholar 

  • Buckles, B. P., & Petry, F. E. (1982). A fuzzy representation of data for relational databases. Fuzzy Sets and Systems, 7(3), 213–226.

    Article  Google Scholar 

  • Claramunt, C., & Thériault, M. (1995). Managing time in GIS an event-oriented approach. In Proceedings of the 1995 International Workshop on Temporal Databases (pp. 23–42). Springer, Berlin, Heidelberg.

    Google Scholar 

  • Cobb, M. A., & Petry, F. E. (1998). Modeling spatial relationships within a fuzzy framework. Journal of the American Society for Information Science, 49(3), 253–266.

    Article  Google Scholar 

  • Du, Z., Jeong, Y. S., Jeong, M. K., & Kong, S. G. (2012). Multidimensional local spatial autocorrelation measure for integrating spatial and spectral information in hyperspectral image band selection. Applied Intelligence, 36(3), 542–552.

    Article  Google Scholar 

  • Gabelaia, D., Kontchakov, R., Kurucz, A., Wolter, F., & Zakharyaschev, M. (2005). Combining spatial and temporal logics: expressiveness vs. complexity. Journal of Artificial Intelligence Research, 23, 167–243.

    Article  MathSciNet  Google Scholar 

  • Gaurav, A., & Alhajj, R. (2006). Incorporating fuzziness in XML and mapping fuzzy relational data into fuzzy XML. In Proceedings of the 2006 ACM Symposium on Applied Computing (pp. 456–460). Dijon, France: ACM.

    Google Scholar 

  • Guesgen, H. W. (2002). Reasoning about distance based on fuzzy sets. Applied Intelligence, 17(3), 265–270.

    Article  Google Scholar 

  • Huang, B., Yi, S., & Chan, W. T. (2004). Spatio-temporal information integration in XML. Future Generation Computer Systems, 20(7), 1157–1170.

    Article  Google Scholar 

  • Jiang, H., Lu, H., & Wang, W. (2004). Efficient processing of XML twig queries with OR-predicates. In Proceedings of the 2004 ACM SIGMOD International Conference on Management of Data (pp. 59–70). Paris, France: ACM.

    Google Scholar 

  • Jin, P., Wan, S., & Yue, L. (2007). A semantic framework for spatiotemporal data representation. In Proceedings of the 2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System (pp. 10–17). Shanghai, China: IEEE.

    Google Scholar 

  • Kimelfeld, B., & Sagiv, Y. (2007). Matching twigs in probabilistic XML. In Proceedings of the 33rd International Conference on Very Large Data Bases (pp. 27–38). Vienna, Austria: VLDB Endowment.

    Google Scholar 

  • Koubarakis, M. (2002). Querying temporal constraint networks: A unifying approach. Applied Intelligence, 17(3), 297–311.

    Article  Google Scholar 

  • Li, Y., Wang, G., Xin, J., Zhang, E., & Qiu, Z. (2009). Holistically twig matching in probabilistic XML. In Proceedings of the 2009 IEEE International Conference on Data Engineering (pp. 1649–1656). Shanghai, China: IEEE.

    Google Scholar 

  • Ma, Z. M., & Yan, L. (2007). Fuzzy XML data modeling with the UML and relational data models. Data & Knowledge Engineering, 63(3), 972–996.

    Article  Google Scholar 

  • Ma, Z. M., Liu, J., & Yan, L. (2010). Fuzzy data modeling and algebraic operations in XML. International Journal of Intelligent Systems, 25(9), 925–947.

    MATH  Google Scholar 

  • Ma, Z. M., Liu, J., & Yan, L. (2011). Matching twigs in fuzzy XML. Information Sciences, 181(1), 184–200.

    Article  MathSciNet  Google Scholar 

  • Mihalcea, R. (2012). CSCE 3110 Data Structures & Algorithm Analysis. University of North Texas. http://www.cs.unt.edu/~rada/CSCE3110.

  • Oliboni, B., & Pozzani, G. (2008). Representing fuzzy information by using XML schema. In Proceedings of the 2008 International Workshop on Database and Expert Systems Applications (pp. 683–687). Turin, Italy: IEEE.

    Google Scholar 

  • Open GIS Consortium Inc. (OGC). (2001). Geography Markup Language (GML).

    Google Scholar 

  • Papadakis, N., Plexousakis, D., & Christodolou, Y. (2012). The ramification problem in temporal databases: A solution implemented in SQL. Applied Intelligence, 36(4), 749–767.

    Article  Google Scholar 

  • Pauly, A., & Schneider, M. (2005). Topological predicates between vague spatial objects. In Proceedings of the 2005 International Symposium on Spatial and Temporal Databases (pp. 418–432). Springer, Berlin, Heidelberg.

    Google Scholar 

  • Peuquet, D. J., & Duan, N. (1995). An event-based spatiotemporal data model (ESTDM) for temporal analysis of geographical data. International Journal of Geographical Information Systems, 9(1), 7–24.

    Article  Google Scholar 

  • Pfoser, D., & Jensen, C. S. (1999). Capturing the uncertainty of moving-object representations. In Proceedings of the 1999 International Symposium on Spatial Databases (pp. 111–131). Springer, Berlin, Heidelberg.

    Google Scholar 

  • Rizzolo, F., & Vaisman, A. A. (2008). Temporal XML: Modeling, indexing, and query processing. The VLDB Journal, 17(5), 1179–1212.

    Article  Google Scholar 

  • Salamat, N., & Zahzah, E. H. (2010). Fusion of fuzzy spatial relations. In Proceedings of the 2010 International Conference on Hybrid Artificial Intelligence Systems (pp. 294–301). Springer, Berlin, Heidelberg.

    Google Scholar 

  • Senellart, P., & Abiteboul, S. (2007). On the complexity of managing probabilistic XML data. In Proceedings of the Twenty-sixth ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems (pp. 283–292). Beijing, China: ACM.

    Google Scholar 

  • Sözer, A., Yazıcı, A., OÄŸuztüzün, H., & TaÅŸ, O. (2008). Modeling and querying fuzzy spatiotemporal databases. Information Sciences, 178(19), 3665–3682.

    Article  Google Scholar 

  • Stefanakis, E. (2001). A unified framework for fuzzy spatio-temporal representation and reasoning. In Proceedings of the 20th International Cartographic Conference (pp. 2678–2687). Beijing, China.

    Google Scholar 

  • Tang, X., & Kainz, W. (2002). Analysis of topological relations between fuzzy regions in a general fuzzy topological space. In Proceedings of the 2002 International Symposium on Geospatial Theory, Processing and Applications (pp. 1–15). Ottawa, Canada.

    Google Scholar 

  • Tang, X., Fang, Y., & Kainz, W. (2006). Fuzzy topological relations between fuzzy spatial objects. In Proceedings of the 2006 International Conference on Fuzzy Systems and Knowledge Discovery (pp. 324–333). Springer, Berlin, Heidelberg.

    Google Scholar 

  • Tossebro, E., & NygÃ¥rd, M. (2002). Uncertainty in spatiotemporal databases. In Proceedings of the 2002 International Conference on Advances in Information Systems (pp. 43–53). Springer, Berlin, Heidelberg.

    Google Scholar 

  • Turowski, K., & Weng, U. (2002). Representing and processing fuzzy information—An XML-based approach. Knowledge-Based Systems, 15(1–2), 67–75.

    Article  Google Scholar 

  • Yan, L., Ma, Z. M., & Liu, J. (2009). Fuzzy data modeling based on XML schema. In Proceedings of the 2009 ACM Symposium on Applied Computing (pp. 1563–1567). Honolulu, Hawaii: ACM.

    Google Scholar 

  • Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338–353.

    Article  MathSciNet  Google Scholar 

  • Zadeh, L. A. (1978). Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets and Systems, 1(1), 3–28.

    Article  MathSciNet  Google Scholar 

  • Zadeh, L. A. (2005). Toward a generalized theory of uncertainty (GTU)—An outline. Information Sciences, 172(1–2), 1–40.

    Article  MathSciNet  Google Scholar 

  • Zadeh, L. A. (2008). Is there a need for fuzzy logic? Information Sciences, 178(13), 2751–2779.

    Article  MathSciNet  Google Scholar 

  • Zhan, F. B., & Lin, H. (2003). Overlay of two simple polygons with indeterminate boundaries. Transactions in GIS, 7(1), 67–81.

    Article  Google Scholar 

  • Zhang, C., Naughton, J., DeWitt, D., Luo, Q., & Lohman, G. (2001). On supporting containment queries in relational database management systems. In Proceedings of the 2001 ACM SIGMOD International Conference on Management of Data (pp. 425–436). Santa Barbara, USA: ACM.

    Google Scholar 

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Authors and Affiliations

  1. College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu, China

    Zongmin Ma

  2. College of Information Science and Engineering, Northeastern University (Qinhuangdao), Qinhuangdao, Hebei, China

    Luyi Bai

  3. College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu, China

    Li Yan

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  1. Zongmin Ma
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  2. Luyi Bai
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  3. Li Yan
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Correspondence to Zongmin Ma .

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Ma, Z., Bai, L., Yan, L. (2020). Determining Topological Relationship of Fuzzy Spatiotemporal Data in XML. In: Modeling Fuzzy Spatiotemporal Data with XML. Studies in Computational Intelligence, vol 894. Springer, Cham. https://doi.org/10.1007/978-3-030-41999-8_5

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