Label Normalization and Lexical Annotation for Schema and Ontology Matching

Schema matching is the problem of finding relationships among concepts across heterogeneous data sources (heterogeneous in format and semantics). The “hidden meaning ” associated with schema labels (i.e. class and attribute names) may be explicated by Lexical Annotation (i.e. annotation with respect to an authoritative lexical thesaurus). The goal of this thesis is to propose, and experimentally evaluate automatic and semi-automatic methods performing lexical annotation of schema labels. In this way, we may add sharable semantics to legacy data sources. Moreover, an-notated labels are a powerful means in order to discover Lexical Relationships among structured and semi-structured data sources. Original methods to automa-tically extract lexical relationships have been developed and their affectiveness for automatic schema matching shown. In this thesis, a novel automatic lexical annotation method called CWSD (Combined Word Sense Disambiguation), which assigns to each schema label on