期刊名称:International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN:2158-107X
电子版ISSN:2156-5570
出版年度:2019
卷号:10
期号:10
页码:461-481
出版社:Science and Information Society (SAI)
摘要:Using domain knowledge and semantics to conduct
effective document retrieval has attracted great attention from
researchers in many different communities. Ultilizing that approach,
we presents the method for designing domain-specific
document retrieval systems, which manages semantic information
related to document content and supports semantic processing
in search. The proposed method integrates components such
as an ontology describing domain knowledge, a database of
document repository, semantic representations for documents;
and advanced search techniques based on measuring semantic
similarity. In this article, a model of domain knowledge for
various information retrieval tasks, called The Classed Keyphrase
based Ontology (CK-ONTO), will be presented in details. We
also present graph-based models for representing documents
together measures for evaluating the semantic relevance for
usage in searching. The above methodology has been used in
designing many real-world applications such as the Job-posting
retrieval system. Evaluation with real-world inspired dataset,
our methods showed noticeable improvements over traditional
retrieval solutions.