Solving matching problems in computer science entails generating alignments between structured data. Well known examples are schema matching, process model matching, ontology alignment, and Web service composition. Design of software systems aimed at solving these problems, and refinement of interim results, are aided by solution quality evaluation measures.
We base our exploration in the schema matching domain. Schema matching is the task of providing correspondences between concepts describing the meaning of data in various heterogeneous, distributed data sources (e.g. attributes in database schemas, tags in XML DTDs, fields in HTML forms, etc.) Schema matching was recognized to be one of the basic operations required by the process of data and schema integration but has since been adopted by a wide range of applications as a basic method for matching various representations of data.
Schema matching research at the Technion starts focuses on introducing new matching theories based on which new and better heuristics for schema matching can be developed. We invest in the development of new evaluation measures for schema matching, as well as developing a model for predicting the performance of machine and human matchers.
OntoBuilder is a matching tool supported by the research group at the Technion. OntoBuilder provides ORE, OntoBuilder Research Environment, which allows researchers access to common schema matching heuristics as well as datasets for performing benchmark empirical evaluation