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Упит dcterms_subject_txt:ontology

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  • Medical Domain Document Classification via Extraction of Taxonomy Concepts from MeSH Ontology

    Mihailo Škorić, Mauro Dragoni (2019)
    This paper is a result of a task that was presented to attendants of Keyword Search in Big Linked Data summer school, that was organized by Vienna University of Technology, under the Keystone COST action in the summer of 2017. It presents a specific approach to the classification via creation of minimal document surrogates based on the US National medical library’s MeSH ontology, which is derived from the Medical Subject Headings thesaurus. In a series of previously classified medically ...
    document classification, MeSH, ontology, information extraction
    ... from the MeSH ontology. Extracted references are used for the classifi- cation within the ontology using a rather sim- ple algorithm and the results are evaluated in compresence to previous manual classification of the same documents. KEYWORDS: document classification, MeSH, ontology, information extraction ...
    ... labels, which is especially important if a local copy of the MeSH ontology is used5 Ontology consists of 56,309 medical concepts, described and systematically classified in a hierarchical tree (Figure 2). The concepts from the ontology are hierarchically collated, and each has an assigned identifier ...
    ... taxonomy from the MeSH ontology and a rule-based system managing the appearance of terms related to con- cepts from the MeSH ontology in the documents to be classified. The course of the experiment can be divided into five follow-up steps. 1. Extraction of taxonomy from MeSH ontology using SPARQL query ...

  • Ontološki model upravljanja rizikom u rudarstvu

    Olivera Kitanović (2021)
    Rudarska proizvodnja obuhvata kompleksne tehnološke sisteme, što nameće potrebu za uspostavljanjem i unapređivanjem sistema upravljanja rizikom. Heterogenost i obim podataka neophodnih za upravljanje rizikom zahtevaju sistem koji ih na fleksibilan način integriše i omogućava njihovo optimalno korišćenje. Osnovni cilj ove disertacije je razvoj ontologije za domen rudarstva i na njoj zasnovanog modela za upravljanje rizikom. Njegova realizacija podrazumeva i implementaciju algoritama ekstrakcije informacija za popunjavanje ontologije, kao i odgovarajuće softversko rešenje. Razvoj modela obuhvata i značajno proširenje rudarskog korpusa, kao ...
    rudarstvo, rizik, upravljanje rizikom, procena rizika, ontologija, semantička mreža, ekstrakcija informacija, upravljanje znanjem, računarska lingvistika
    ... and Maria Pia Di Gregorio. 2010. “Ontology Based Risk Management.” In Decision Theory and Choices: A Complexity Approach, 235–51. Springer. Noy, Natalya F, Deborah L McGuinness, and others. 2001. Ontology Development 101: A Guide to Creating Your First Ontology. Stanford knowledge systems laboratory ...
    ... use. The main goal of this dissertation is to develop an ontology for the mining domain and a risk management model based on it. Its realization includes the implementation of information extraction algorithms for improving the ontology, as well as an appropriate software solution. The development ...
    ... Information technology tools were used for model development: UML for concept modeling, OWL for ontology development, SWRL rules for inference mechanism, query languages CQL for corpus and SPARQL for ontology. The research results show that it is possible to formalize information and knowledge about ...