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Discovery of Schema Information from a Forest of Selectively Labeled Ordered Trees
| Content Provider | Semantic Scholar |
|---|---|
| Author | Seo, Dong-Yal Lee, Dong-Ha Lee, Kyung-Mee |
| Copyright Year | 1997 |
| Abstract | * This paper was supported by ’95 SPECIAL FUND for U NIVERSITY RESEARCH INSTITUTE, Korea Research Foundation. Abstract The main focus of our work is to discover an object -oriented schema information from a set of semistructured data. We develop schema extraction a lgorithms and a data model for semistructured data . Our data model is an improved version of the data forest model. We modify the ordered labeled trees of the data forest model to allow selectively unlabeled vertices. The unlabeled vertices represent set structures whi ch are syntactically incomplete in the data forest model. The efforts on schema discovery give a major distinction between our study and former ones. Schema extraction algorithms discover structural schema information from a set of semistructured data represented in our modified dat a forest model. We can extract identifiable classes, their attributes, and a composition hierar chy with the proposed algorithms. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.research.att.com/~suciu/WORKSHOP-PAPERS/paper08.ps |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
