Using Pseudo Feedback to Improve Cross-Lingual Ontology Mapping

Abstract

Translation techniques are often employed by cross-lingual ontology mapping (CLOM) approaches to turn a cross-lingual mapping problem into a monolingual mapping problem which can then be solved by state of the art monolingual ontology matching tools. However in the process of doing so, noisy translations can compromise the quality of the matches generated by the subsequent monolingual matching techniques. In this paper, a novel approach to improve the quality of cross-lingual ontology mapping is presented and evaluated. The proposed approach adopts the pseudo feedback technique that is similar to the well understood relevance feedback mechanism used in the field of information retrieval. It is shown through the evaluation that pseudo feedback can improve the matching quality in a CLOM scenario.