DocumentCode :
3567549
Title :
Network of Natural Terms Hierarchy as a Lightweight Ontology
Author :
Lande, Dmitry ; Snarskii, Andrey ; Yagunova, Elena ; Pronoza, Ekaterina ; Volskaya, Svetlana
Author_Institution :
Inst. for Inf. Recording, NTUU “Kiev Polytech. Inst.”, Kiev, Ukraine
fYear :
2014
Firstpage :
16
Lastpage :
23
Abstract :
This paper describes the construction methodology of a network of natural terms hierarchy based on the analysis of a homogeneous or heterogeneous text corpus. It also presents a criterion for the evaluation of paper relevance to a particular scientific conference. The proposed method is illustrated by the examples from the heterogeneous corpus of the STIDS 2013 conference proceedings.
Keywords :
natural language processing; ontologies (artificial intelligence); scientific information systems; text analysis; STIRS 2013 conference; heterogeneous text corpus analysis; homogeneous text corpus analysis; lightweight ontology; natural term hierarchy network; paper relevance evaluation; scientific conference; Analytical models; Big data; Data models; Ontologies; Semantics; Social network services; compactified horizontal visibility graph; language network; scientific trend; term hierarchy;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Artificial Intelligence (MICAI), 2014 13th Mexican International Conference on
Print_ISBN :
978-1-4673-7010-3
Type :
conf
DOI :
10.1109/MICAI.2014.9
Filename :
7222837
Link To Document :
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