Abstract
When integrating XML documents from autonomous databases, exact joins often fail for the data items representing the same real world object may not be exactly the same. Thus the join must be approximate. Tree-edit-distance-based join methods have high join quality but low efficiency. Comparatively, other methods with higher efficiency cannot perform the join as effectively as tree edit distance does.
To keep the balance between efficiency and effectiveness, in this paper, we propose a novel method to approximately join XML documents. In our method, trees are transformed to g-strings with each entry a tiny subtree. Then the distance between two trees is evaluated as the g-string distance between their corresponding g-strings. To make the g-string based join method scale to large XML databases, we propose the g-bag distance as the lower bound of the g-string distance. With g-bag distance, only a very small part of g-string distance need to be computed directly. Thus the whole join process can be done very efficiently. We theoretically analyze the properties of the g-string distance. Experiments with synthetic and various real world data confirm the effectiveness and efficiency of our method and suggest that our technique is both scalable and useful.
Supported by the National Science Foundation of China (No 60703012, 60773063), the NSFC-RGC of China(No. 60831160525), National Grant of Fundamental Research 973 Program of China (No.2006CB303000), National Grant of High Technology 863 Program of China (No. 2009AA01Z149), Key Program of the National Natural Science Foundation of China (No. 60933001), National Postdoctor Foundtaion of China (No. 20090450126), Development Program for Outstanding Young Teachers in Harbin Institute of Technology (no. HITQNJS.2009.052).
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References
Augsten, N., Böhlen, M.H., Dyreson, C.E., Gamper, J.: Approximate joins for data-centric xml. In: ICDE, pp. 814–823 (2008)
Augsten, N., Böhlen, M.H., Gamper, J.: Approximate matching of hierarchical data using pq-grams. In: VLDB, pp. 301–312 (2005)
Augsten, N., Böhlen, M.H., Gamper, J.: The pq-gram distance between ordered labeled trees. ACM Trans. Database Syst. 35(1) (2010)
Bille, P.: A survey on tree edit distance and related problems. Theor. Comput. Sci. 337(1-3), 217–239 (2005)
Demaine, E.D., Mozes, S., Rossman, B., Weimann, O.: An optimal decomposition algorithm for tree edit distance. In: Arge, L., Cachin, C., Jurdziński, T., Tarlecki, A. (eds.) ICALP 2007. LNCS, vol. 4596, pp. 146–157. Springer, Heidelberg (2007)
Garofalakis, M.N., Kumar, A.: Xml stream processing using tree-edit distance embeddings. ACM Trans. Database Syst. 30(1), 279–332 (2005)
Guha, S., Jagadish, H.V., Koudas, N., Srivastava, D., Yu, T.: Approximate xml joins. In: SIGMOD Conference, pp. 287–298 (2002)
Kailing, K., Kriegel, H.-P., Schönauer, S., Seidl, T.: Efficient similarity search for hierarchical data in large databases. In: Bertino, E., Christodoulakis, S., Plexousakis, D., Christophides, V., Koubarakis, M., Böhm, K., Ferrari, E. (eds.) EDBT 2004. LNCS, vol. 2992, pp. 676–693. Springer, Heidelberg (2004)
Klein, P.N.: Computing the edit-distance between unrooted ordered trees. In: Bilardi, G., Pietracaprina, A., Italiano, G.F., Pucci, G. (eds.) ESA 1998. LNCS, vol. 1461, pp. 91–102. Springer, Heidelberg (1998)
Kuboyama, T.: Matching and Learning in Trees (2007)
Shapiro, B.A., Zhang, K.: Comparing multiple rna secondary structures using tree comparisons. Computer Applications in the Biosciences 6(4), 309–318 (1990)
Tai, K.-C.: The tree-to-tree correction problem. J. ACM 26(3), 422–433 (1979)
Tatikonda, S., Parthasarathy, S.: Hashing Tree-Structured Data: Methods and Applications. In: ICDE (to appear, 2010)
Valiente, G.: An efficient bottom-up distance between trees. In: SPIRE, pp. 212–219 (2001)
van Rijsbergen, C.J.: Information Retrieval. Butterworth, London (1979)
Yang, R., Kalnis, P., Tung, A.K.H.: Similarity evaluation on tree-structured data. In: SIGMOD Conference, pp. 754–765 (2005)
Zhang, K., Shasha, D.: Simple fast algorithms for the editing distance between trees and related problems. SIAM J. Comput. 18(6), 1245–1262 (1989)
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Li, F., Wang, H., Zhang, C., Hao, L., Li, J., Gao, H. (2010). Approximate Joins for XML Using g-String. In: Lee, M.L., Yu, J.X., Bellahsène, Z., Unland, R. (eds) Database and XML Technologies. XSym 2010. Lecture Notes in Computer Science, vol 6309. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15684-7_2
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DOI: https://doi.org/10.1007/978-3-642-15684-7_2
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