Abstract
In recent years there has been an increased interest in managing data that does not conform to traditional data models, like the relational or object oriented model. The reasons for this non-conformance are diverse. On the one hand, data may not conform to such models at the physical level: it may be stored in data exchange formats, fetched from the Web, or stored as structured files. One the other hand, it may not conform at the logical level: data may have missing attributes, some attributes may be of different types in different data items, there may be heterogeneous collections, or the schema may be too complex or changes too often. The term semistructured data has been used to refer to such data. The semistructured data model consists of an edge-labeled graph, in which nodes correspond to objects and edges to attributes or values. Figure 1 illustrates a semistructured database providing information about a city.
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References
S. Abiteboul, D. Quass, J. McHugh, J.Widom, and J. Wiener. The Lorel query language for semistructured data. International Journal on Digital Libraries, 1(1):68–88, April 1997.
Serge Abiteboul. Querying semi-structured data. In ICDT, 1997.
Serge Abiteboul and Victor Vianu. Generic computation and its complexity. In Proceedings of 23rd ACM Symposium on the Theory of Computing, 1991.
Elisa Bertion and Won Kim. Indexing techniques for queries on nested objects. IEEE Transactions on Knowledge and Data Engineering, 1(2):196–214, June 1989.
Adam Buchsbaum, Paris Kanellakis, and Jeffrey Scott Vitter. A data structure for arc insertion and regular path finding. Annals of Mathematics and Artificial Intelligence, 3:187–210, 1991.
Peter Buneman, Susan Davidson, Mary Fernandez, and Dan Suciu. Adding structure to unstructured data. In Proceedings of the International Conference on Database Theory, pages 336–350, Deplhi, Greece, 1997. Springer Verlag.
Peter Buneman, Susan Davidson, Gerd Hillebrand, and Dan Suciu. A query language and optimization techniques for unstructured data. In Proceedings of ACM-SIGMOD International Conference on Management of Data, 1996.
V. Christophides, S. Abiteboul, S. Cluet, and M. Scholl. From structured documents to novel query facilities. In Richard Snodgrass and Marianne Winslett, editors, Proceedings of 1994 ACM SIGMOD International Conference on Management of Data, Minneapolis, Minnesota, May 1994.
P. Flajolet and R. Sedgewick. Digital search trees revisited. SIAM Journal on Computing, 15:748–767, 1986.
Harold Gabow and Robert Tarjan. Faster scaling algorithms for network problems. SIAM Journal of Computing, 18(5):1013–1036, 1989.
Roy Goldman and Jennifer Widom. DataGuides: enabling query formulation and optimization in semistructured databases. In VLDB, September 1997.
G. Gonnet. Efficient searching of text and pictures (extended abstract). Technical Report OED-88-02, University of Waterloo, 1988.
Monika Henzinger, Thomas Henzinger, and Peter Kopke. Computing simulations on finite and infinite graphs. In Proceedings of 20th Symposium on Foundations of Computer Science, pages 453–462, 1995.
Alfons Kemper and Guido Moerkkotte. Access support relations: an indexing method for object bases. Information Systems, 17(2):117–145, 1992.
Alon Levy, Alberto Mendelzon, Yehoshua Sagiv, and Divesh Srivastava. Answering queries using views. In Proceedings of the 14th Symposium on Principles of Database Systems, San Jose, CA, June 1995.
A. Mendelzon, G. Mihaila, and T. Milo. Querying the world wide web. In Proceedings of the Fourth Conference on Parallel and Distributed Information Systems, Miami, Florida, December 1996.
Robin Milner. Communication and concurrency. Prentice Hall, 1989.
S. Nestorov, S. Abiteboul, and R. Motwani. Inferring structure in semistructured data. In Proceedings of the Workshop on Management of Semi-structured Data, 1997.
S. Nestorov, J. Ullman, J. Wiener, and S. Chawathe. Representative objects: concise representation of semistructured, hierarchical data. In ICDE, 1997.
Robert Paige and Robert Tarjan. Three partition refinement algorithms. SIAM Journal of Computing, 16:973–988, 1987.
A. Salminen and F. W. Tompa. Pat expressions: an algebra for text search. In Papers in Computational Lexicography: COMPLEX’92, pages 309–332, 1992.
L. J. Stockmeyer and A.R. Meyer. Word problems requiring exponential time. In 5th STOC, pages 1–9. ACM, 1973.
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Milo, T., Suciu, D. (1999). Index Structures for Path Expressions. In: Beeri, C., Buneman, P. (eds) Database Theory — ICDT’99. ICDT 1999. Lecture Notes in Computer Science, vol 1540. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-49257-7_18
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DOI: https://doi.org/10.1007/3-540-49257-7_18
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