Please use this identifier to cite or link to this item:
|Title:||Discovering structural association of semistructured data|
|Authors:||Wang, K. |
|Citation:||Wang, K., Liu, H. (2000). Discovering structural association of semistructured data. IEEE Transactions on Knowledge and Data Engineering 12 (3) : 353-371. ScholarBank@NUS Repository. https://doi.org/10.1109/69.846290|
|Abstract:||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.|
|Source Title:||IEEE Transactions on Knowledge and Data Engineering|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Aug 18, 2018
WEB OF SCIENCETM
checked on Jul 16, 2018
checked on Jun 2, 2018
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.