TY - JOUR
TI - Review of Tools for Semantics Extraction: Application in Tsunami
Research Domain
AU - Babic, Frantisek
AU - Bures, Vladimir
AU - Cech, Pavel
AU - Husakova,
AU - Martina
AU - Mikulecky, Peter
AU - Mls, Karel
AU - Nachazel, Tomas and
AU - Ponce, Daniela
AU - Stekerova, Kamila
AU - Triantafyllou, Ioanna and
AU - Tucnik, Petr
AU - Zanker, Marek
JO - INFORMATIONS
PY - 2022
VL - 13
TODO - 1
SP - null
PB - MDPI
SN - null
TODO - 10.3390/info13010004
TODO - semantics; taxonomy; ontology; ontology learning; knowledge extraction;
natural language processing; tool; tsunami
TODO - 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.
ER -