Extraction of Terms Related to Named Rivers

Bibliographic Data

ID5900170
AuthorsJuan Rojas-Garcia (0000-0002-7611-1386, Universidad de Granada, corresponding author), Paul Faber (0000-0003-0581-0005, Universidad de Granada)
Year2019
Volume4
Issue3
Pages46
Publication date2019-06-27
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueLanguages (JOURNAL)
Journal identifiersISSN: 2226-471X • E-ISSN: 2226-471X
PublisherMDPI AG (PUBLISHER • IT)
DOI10.3390/languages4030046
OpenAlexW2955446412
LanguageEN
References cited19

EcoLexicon is a terminological knowledge base on environmental science, whose design permits the geographic contextualization of data. For the geographic contextualization of landform concepts, this paper presents a semi-automatic method for extracting terms associated with named rivers (e.g., Mississippi River). Terms were extracted from a specialized corpus, where named rivers were automatically identified. Statistical procedures were applied for selecting both terms and rivers in distributional semantic models to construct the conceptual structures underlying the usage of named rivers. The rivers sharing associated terms were also clustered and represented in the same conceptual network. The results showed that the method successfully described the semantic frames of named rivers with explanatory adequacy, according to the premises of Frame-Based Terminology

Cartography · Construct (python library · Contextualization · Data mining · Frame (networking · Geography · Information retrieval · Interpretation (philosophy · Landform · Linguistics · Natural language processing · Semantic network · Terminology · Computer Science · Lexicography and Language Studies · linguistics and terminology studies · Natural Language Processing Techniques · Artificial Intelligence

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