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Issue No. 03 - May/June (2000 vol. 12)
ISSN: 1041-4347
pp: 353-371
<p><b>Abstract</b>—Many semistructured objects are similarly, though not identically, structured. We study the problem of discovering “typical” substructures of a collection of semistructured objects. The discovered structures can serve the following purposes: 1) the “table-of-contents” for gaining general information of a source, 2) a road map for browsing and querying information sources, 3) a basis for clustering documents, 4) partial schemas for providing standard database access methods, and 5) user/customer's interests and browsing patterns. The discovery task is impacted by structural features of semistructured data in a nontrivial way and traditional data mining frameworks are inapplicable. We define this discovery problem and propose a solution.</p>
Association rule, database, data mining, knowledge discovery, semistructured data, web mining.

K. Wang and H. Liu, "Discovering Structural Association of Semistructured Data," in IEEE Transactions on Knowledge & Data Engineering, vol. 12, no. , pp. 353-371, 2000.
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