Database Schema Matching
a Corpus-based Approach
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This book presents a method for database schemamatching, the problem of identifying elements of twogiven schemas that correspond to each other. Schemamatching is useful in e-commerce exchanges, in dataintegration/warehousing, and in Semantic Webapplications. It first presents two corpus-basedmethods: one method is for determining the semanticsimilarity of two target words and the other is forautomatic word segmentation. Then it presents aname-based element-level database schema matchingmethod that exploits both the semantic similarity andthe word segmentation methods.
This book presents a method for database schema
matching, the problem of identifying elements of two
given schemas that correspond to each other. Schema
matching is useful in e-commerce exchanges, in data
integration/warehousing, and in Semantic Web
applications. It first presents two corpus-based
methods: one method is for determining the semantic
similarity of two target words and the other is for
automatic word segmentation. Then it presents a
name-based element-level database schema matching
method that exploits both the semantic similarity and
the word segmentation methods.
matching, the problem of identifying elements of two
given schemas that correspond to each other. Schema
matching is useful in e-commerce exchanges, in data
integration/warehousing, and in Semantic Web
applications. It first presents two corpus-based
methods: one method is for determining the semantic
similarity of two target words and the other is for
automatic word segmentation. Then it presents a
name-based element-level database schema matching
method that exploits both the semantic similarity and
the word segmentation methods.
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