TRC-Matcher and enhanced TRC-Matcher. New Tools for Automatic XML Schema Matching

Modern society depends on the access to a wide range of information that is located in heterogeneous data sources. Schema matching is a task of finding relationships among data source elements automatically. However, most of the existing schema matching software are semi-automatic meaning that they need a lot of interaction from an expert familiar with the systems being integrated. In this work, we propose a new hybrid matcher algorithm, called TRC-matcher, that is targeted for matching business oriented XML schemas with none or minor user assistance. When compared to previously published schema matching methods, the efficiency of the new algorithm is based on a new content profiling algorithm and on intelligent combination of matching results of multiple matching algorithms. In addition, an enhanced version of the TRC-Matcher is introduced that combines machine learning methods together with few new matching algorithms.

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