Intelligent Information Retrieval within Digital Library using Domain Ontology

Abstract

One kind of information retrieval system is a digital library. Keyword searches are often problematic for the current information
retrieval technologies. To address this, we put forth a model that makes use of a metadata case base and a concept-based
approach (ontology). The user’s query is used to discover domain ideas, which are then expanded upon in this model. By
suggesting a conceptual question expansion for intelligent concept-based retrieval, the technology hopes to help make search
results from digital libraries more relevant. The idea of ontology, with its wealth of semantics and common concepts, has to
be imported. By shifting the focus from keyword matching to semantics matching, domain specific ontology may help enhance
information retrieval from a strictly keyword-based approach to one that is more grounded on lay knowledge or concepts. Two
methods exist for retrieving metadata: one uses domain ontology for query expansion techniques, while the other introduces a
case-based similarity measure using the Case Based Reasoning (CBR) method. In comparison to other methods, including the
conventional technique and query expansion utilizing general purpose ontology, the results demonstrate significant gains.