Ontology-Based Conceptualisation of Text Mining Practice Areas for Education

Husáková, Martina

doi:10.1007/978-3-030-28374-2_46

Cited by 1 publication

(2 citation statements)

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“…Two categories of articles were found during the investigation of the WOS scientific database: research articles (36) and reviews (2). The systematic study of journal articles, available in the ScienceDirect and WOS (2016-2021), shows that no review mentions any experience with tools, for example: "Is a tool available during writing the paper?…”

Section: Discussion and Future Directionsmentioning

confidence: 99%

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Review of Tools for Semantics Extraction: Application in Tsunami Research Domain

et al. 2021

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Immense numbers of textual documents are available in a digital form. Research activities are focused on methods of how to speed up their processing to avoid information overloading or to provide formal structures for the problem solving or decision making of intelligent agents. Ontology learning is one of the directions which contributes to all of these activities. The main aim of the ontology learning is to semi-automatically, or fully automatically, extract ontologies—formal structures able to express information or knowledge. The primary motivation behind this paper is to facilitate the processing of a large collection of papers focused on disaster management, especially on tsunami research, using the ontology learning. Various tools of ontology learning are mentioned in the literature at present. The main aim of the paper is to uncover these tools, i.e., to find out which of these tools can be practically used for ontology learning in the tsunami application domain. Specific criteria are predefined for their evaluation, with respect to the “Ontology learning layer cake”, which introduces the fundamental phases of ontology learning. ScienceDirect and Web of Science scientific databases are explored, and various solutions for semantics extraction are manually “mined” from the journal articles. ProgrammableWeb site is used for exploration of the tools, frameworks, or APIs applied for the same purpose. Statistics answer the question of which tools are mostly mentioned in these journal articles and on the website. These tools are then investigated more thoroughly, and conclusions about their usage are made with respect to the tsunami domain, for which the tools are tested. Results are not satisfactory because only a limited number of tools can be practically used for ontology learning at present.

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Section: Discussion and Future Directionsmentioning

confidence: 99%

“…Different approaches and tools exist for (semi-)automated processing of texts [2]. If a user is familiar with programming, various computational libraries, frameworks, or application programming interfaces (APIs) can be used for detection and extraction semantics from texts.…”

Section: Introductionmentioning

confidence: 99%