Building an Integrated Database and Wordnet for Semantic Search

Student: CHISOM GABRIEL OKEREKE (Project, 2025)
Department of Industrial Mathematics
Federal University of Technology, Owerri, Imo State

Abstract

Semantic integration of heterogeneous databases requires that user queries are
understood semantically and can be related to the real contents of underlying
databases. The state of art on data integration is focusing on using ontologies which
is described as a formal and explicit conceptualization, as a semantic foundation for
data integration. Unlike the previous research that considered the databases to have
a well structured ontologies, this thesis employs WordNet lexical database to mine
for synonyms from WordNet synsets into cluster. A query reformulation algorithm
is proposed to reformulate the user query based on the retrieved synonyms and then
lookup for all the queries in the database(s). The implementation turned out to be
effective in practical applications, with a particular set of data, as the system is able
to identify terms correctly based on synset, while previous methods relying only on
available terms in the WordNet, this thesis can handle an unknown term by the
WordNet by inserting new term into the existing synset in the WordNet database.
Though, the evaluation results show that the proposed approach improves recall, but
the system incurs high execution time as the number of table increases.

Keywords
Semantic Search Data Integration WordNet Query Reformulation Synonyms Cluster Algorithm Heterogeneous Databases Ontology Synset Lingo Algorithm JDBC
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