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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 10 Issue 10, 2019.
Abstract: Using domain knowledge and semantics to con-duct e‡ective document retrieval has attracted great attention from researchers in many di‡erent communities. Ultilizing that approach, we presents the method for designing domain-speciÿc document retrieval systems, which manages semantic information related to document content and supports se-mantic processing in search. ⁄e proposed method integrates components such as an ontology describing domain knowl-edge, a database of document repository, semantic represen-tations 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 ⁄e 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. ⁄e 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.
ThanhThuong T. Huynh, TruongAn PhamNguyen and Nhon V. Do, “A Method for Designing Domain-Specific Document Retrieval Systems using Semantic Indexing” International Journal of Advanced Computer Science and Applications(IJACSA), 10(10), 2019. http://dx.doi.org/10.14569/IJACSA.2019.0101063
@article{Huynh2019,
title = {A Method for Designing Domain-Specific Document Retrieval Systems using Semantic Indexing},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2019.0101063},
url = {http://dx.doi.org/10.14569/IJACSA.2019.0101063},
year = {2019},
publisher = {The Science and Information Organization},
volume = {10},
number = {10},
author = {ThanhThuong T. Huynh and TruongAn PhamNguyen and Nhon V. Do}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.