Schema Matching Using Directed Graph Matching

摘要

Integration of data from multiple sources has gained importance as data and the data providers explode at a faster rate. Schema matching is considered an important step in integrating data from multiple sources. Most of the available techniques for automated schema matching require interpretation of attribute names and data values. Such techniques fail when the data sources have incomprehensible attribute names and data values. An alternative schema matching technique, which uses statistics from the schema instances and does not require value interpretations, is proposed in this paper. In this work, functional dependency (FD) relationships between attributes of two schemas are represented in the form of a directed dependency graph. A primitive directed graph matching algorithm is used to find the matching between the two dependency graphs and therefore to find the corresponding attributes of the two schemas. The experimental results show that the proposed approach increases the accuracy of matching as it uses fine grained functional dependency relationships between attributes to compare two schemas.