Abstract
Semi-structured data are typically represented in the form of labeled directed graphs. They are self-describing and schemaless. The lack of a schema renders query processing over semi-structured data expensive. To overcome this predicament, some researchers proposed to use the structure of the data for schema representation. Such schemas are commonly referred to as graph schemas. Nevertheless, since semi- structured data are irregular and frequently subjected to modifications, it is costly to construct an accurate graph schema and worse still, it is difficult to maintain it thereafter. Furthermore, an accurate graph schema is generally very large, hence impractical. In this paper, an approximation approach is proposed for graph schema extraction. Approximation is achieved by summarizing the semi-structured data graph using an incremental clustering method. The preliminary experimental results have shown that approximate graph schemas were more compact than the conventional accurate graph schemas and promising in query evaluation that involved regular path expressions.
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References
S. Abiteboul. Querying semi-structured data. In Proceedings of the International Conference On Database Theory, 1997.
S. Abiteboul, D. Quass, J. McHugh, J. Widom, and J. Wiener. The lorel query language for semi-structured data. International Journal on Digital Libraries, 1(1):68–88, 1997.
P. Bueman, S. Davidson, G. Hillebrand, and D. Suciu. A query language and optimization techniques for unstructured data. In Proceedings of ACM SIGMOD International Conference on Management of Data, 1996.
P. Buneman. Semistructured data. In Proceedings of PODS, 1997.
P. Buneman, S. Davidson, M. Fernandez, and D. Suciu. Adding structure to unstructured data. In Proceedings of International Conference on Database Theory, 1997.
V. Christophides, S. Cluet, and G. Moerkotte. Evaluating queries with generalized path expressions. In Proceedings of ACM SIGMOD International Conference on Management of Data, 1996.
M. Fernandez and D. Suciu. Optimizing regular path expressions using graph schemas. In Proceedings of International Conference on Data Engineering, 1998.
D. Fisher. Knowledge acquisition via incremental conceptual clustering. In J. Shavlik and T. Dietterich, editors, Readings in Machine Learning. Morgan Kaufmann Publishers, 1990.
G. Gardarin, J. Gruser, and Z. Tang. Cost-based selection of path expression processing algorithms in object-oriented databases. In Proceedings of the 22nd International Conference on Very Large Data Bases, 1996.
R. Goldman and J. Widom. Dataguides: Enabling query formulation and optimization in semistructured databases. In Proceedings of the 23rd International Conference on Very Large Data Bases, 1997.
R. Goldman and J. Widom. Approximate dataguides. Technical report, Stanford University, 1998.
G. Graefe. Query evaluation techniques for large databases. ACM Computing Surveys, 25(2):73–170, 1993.
D. Konopnicki and O. Shmueli. W3qs:a query system for the world wide web. In Proceedings of the International Conference on Very Large Data Bases, 1995.
J. McHugh and J. Widom. Compile-time path expansion in lore. Technical report, Stanford University, 1998.
A. Mendelzon, G. Mihaila, and T. Milo. Querying the world wide web. In Proceedings of the Fourth Conference on Parallel and Distributed Information Systems, 1996.
A. Mendelzon and P. Wood. Finding regular simple paths in graph databases. SIAM Journal of Computing, 24(6):1235–1258, 1995.
S. Nestorov, S. Abiteboul, and R. Motwani. Inferring structure in semistructured data. In Proceedings of the Workshop on Management of Semistructured Data, 1997.
S. Nestorov, S. Abiteboul, and R. Motwani. Extracting schema from semistructured data. In Proceedings of ACM SIGMOD International Conference on Management of Data, 1998.
S. Nestorov, J. Ullman, J. Wiener, and S. Chawathe. Representative objects: Concise representations of semistructured, hierarchical data. In Proceedings of International Conference on Data Engineering, 1997.
Y. Papakonstantinou, H. Garcia-Molina, and J. Widom. Object exchange across heterogeneous information sources. In Proceedings of International Conference on Data Engineering, 1995.
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Wang, Q.Y., Yu, J.X., Wong, KF. (2000). Approximate Graph Schema Extraction for Semi-structured Data. In: Zaniolo, C., Lockemann, P.C., Scholl, M.H., Grust, T. (eds) Advances in Database Technology — EDBT 2000. EDBT 2000. Lecture Notes in Computer Science, vol 1777. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46439-5_21
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DOI: https://doi.org/10.1007/3-540-46439-5_21
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