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Submission: On August 19 via manual from AT — Scanned from AT
Submission: On August 19 via manual from AT — Scanned from AT
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BROWSE PREPRINTS COVID-19 PREPRINTS PROTOCOLS VIDEOS JOURNALS TOOLS & SERVICES OVERVIEW DIGITAL EDITING PROFESSIONAL EDITING BADGES RESEARCH PROMOTION YOUR CART ABOUT PREPRINT PLATFORM IN REVIEW EDITORIAL POLICIES OUR TEAM ADVISORY BOARD BLOG HELP CENTER SIGN IN Submit a Preprint Cite Share Download PDF Research Article INTELLIGENT ONTOLOGY ALIGNMENT TO IMPROVE SEMANTIC DATA INTEGRATION ACROSS RESEARCH DOMAINS IN BIOMEDICINE Muhammad Shoaib Malik, Esther Thea Inau This is a preprint; it has not been peer reviewed by a journal. https://doi.org/10.21203/rs.3.rs-3221032/v1 This work is licensed under a CC BY 4.0 License STATUS: Under Review VERSION 1 posted 17 Aug, 2023 3 You are reading this latest preprint version ABSTRACT Ontology alignment is a key component of semantic web interoperability, with a long history of applications in traditional data integration tasks that address the problem of semantic heterogeneity. Ontology alignment tools take two ontologiesas input and determine alignments as output i.e. a set of correspondences between semantically related units of these ontologies. These correspondences can then be used to merge ontologies, link data across knowledge domains, answer semantic queries, navigate through knowledge graphs, and many more. The process of determining alignments, called matching, therefore is a basic requirement for linking knowledge across scientific domains covered by one or more ontologies. A matching exists if entities from different ontologies are semantically equivalent. The goal of this study is to find all semantically equivalent entity pairs given a source ontology Os and a target ontology Ot, each consisting of a set of entities. We propose to use Inverse Document Frequency (IDF) and Jaccard distance to find candidate entities with high precision and less computational effort. Our goal to cross-link different research fields in the biomedical and clinical domains. ontology alignment semantic web data integration semantic heterogeneity FULL TEXT ADDITIONAL DECLARATIONS Cite Share Download PDF STATUS: Under Review VERSION 1 posted 17 Aug, 2023 * Editor assigned by journal 13 Aug, 2023 * Submission checks completed at journal 13 Aug, 2023 * First submitted to journal 31 Jul, 2023 You are reading this latest preprint version BADGES 0 CITATIONS See more ENGAGEMENT 9 views COMMENTS 0 Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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