Synonyms
Extended node tree; Access method, high‐dimensional; Split, overlap-free; R‑tree; Rectangle, minimum bounding; Rectangle, hyper-
Definition
The X‑tree (eXtended node tree) [1] is a spatial access method [2] that supports efficient query processing for high‐dimensional data. It supports not only point data but also extended spatial data. The X‑tree provides overlap-free split whenever it is possible without allowing the tree to degenerate; otherwise, the X‑tree uses extended variable size directory nodes, so-called supernodes. The X‑tree may be seen as a hybrid of a linear array-like and a hierarchical R‑tree-like directory.
Historical Background
Recommended Reading
Berchtold, S., Keim, D., Kriegel, H.P.: The X‑tree: An index structure for high‐dimensional data. In: Proc. 22th International Conference on Very Large Databases (VLDB'96), pp. 28–39. Morgan Kaufmann, San Francisco, CA, USA (1996)
Böhm, C., Berchtold, S., Keim, D.: Searching in high‐dimensional spaces: Index structures for improving the performance of multimedia databases. ACM Computing Surveys 33(3), 322–373 (2001)
Guttman, A.: R‑trees: A dynamic index structure for spatial searching. In: Proc. ACM International Conference on Management of Data (SIGMOD'84), pp 47–57. ACM Press, New York, NY, USA (1994)
Beckmann, N., Kriegel, H.-P., Schneider, R., Seeger, B.: The R*‑tree: An efficient and robust access method for points and rectangles. In: Proc. ACM International Conference on Management of Data (SIGMOD'90), pp. 322–331. ACM Press, New York, NY, USA (1990)
Faloutsos, C.: Searching Multimedia Databases by Content. Kluwer Academic Publishers, Norwell, MA, USA (1996)
Berchtold, B., Keim, D., Kriegel, H.-P.: Using extended feature objects for partial similarity retrieval. The VLDB Journal 6(4), 333–348 (1997)
Bustos, B., Keim, D., Saupe, D., Schreck, T., Vranić, D.: Feature-based similarity search in 3D object databases. ACM Computing Surveys 37(4), 345–387 (2005)
Shoichet, B.K., Bodian, D.L., Kuntz, I.D.: Molecular docking using shape descriptors. Journal of Computational Chemistry 13(3), 380–397 (1992)
Keim, D.: Efficient geometry-based similarity search of 3D spatial databases. In: Proc. ACM International Conference on Management of Data (SIGMOD'99), pp. 419–430. ACM Press, New York, NY, USA (1999)
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Baeza-Yates, R., Ribeiro-Neto, B.: Modern Information Retrieval. Addison-Wesley Longman Publishing Co. Inc., Boston, MA, USA (1999)
Shawney, H., Hafner, J.: Efficient Color Histogram Indexing. In: Proc. International Conference on Image Processing, pp. 66–70. IEEE Computer Society, Los Alamitos, CA, USA (1994)
Jagadish, H.V.: A retrieval technique for similar shapes. In: Proc. ACM International Conference on Management of Data (SIGMOD'91), pp. 208–217. ACM Press, New York, NY, USA (1991)
Wallace, T., Wintz, P.: An efficient three‐dimensional aircraft recognition algorithm using normalized fourier descriptors. Computer Graphics and Image Processing 13, 99–126 (1980)
Kukich, K.: Techniques for automatically correcting words in text. ACM Computing Surveys 24(4), 377–440 (1992)
Murase, H., Nayar, S.K.: Three‐dimensional object recognition from appearance‐parametric eigenspace method. Systems and Computers in Japan 26(8), 45–54 (1995)
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© 2008 Springer-Verlag
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Keim, D., Bustos, B., Berchtold, S., Kriegel, HP. (2008). Indexing, X-Tree. In: Shekhar, S., Xiong, H. (eds) Encyclopedia of GIS. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-35973-1_620
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DOI: https://doi.org/10.1007/978-0-387-35973-1_620
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