Word2Vec과 WordNet 기반 불확실성 단어 간의 네트워크 분석에 관한 연구 (Network Analysis between Uncertainty Words based on Word2Vec and WordNet)

허고은 (Heo Go Eun)

doi:10.4275/KSLIS.2019.53.3.247

Network Analysis between Uncertainty Words based on Word2Vec and WordNet

Journal of the Korean Society for Library and Information Science
2019, 53(3), pp.247-271
DOI : 10.4275/KSLIS.2019.53.3.247
Publisher : 한국문헌정보학회
Research Area : Interdisciplinary Studies > Library and Information Science
Received : July 16, 2019
Accepted : August 16, 2019
Published : August 31, 2019

Heo Go Eun ¹

¹연세대학교

Excellent Accredited

ABSTRACT

Uncertainty in scientific knowledge means an uncertain state where propositions are neither true or false at present. The existing studies have analyzed the propositions written in the academic literature, and have conducted the performance evaluation based on the rule based and machine learning based approaches by using the corpus. Although they recognized that the importance of word construction, there are insufficient attempts to expand the word by analyzing the meaning of uncertainty words. On the other hand, studies for analyzing the structure of networks by using bibliometrics and text mining techniques are widely used as methods for understanding intellectual structure and relationship in various disciplines. Therefore, in this study, semantic relations were analyzed by applying Word2Vec to existing uncertainty words. In addition, WordNet, which is an English vocabulary database and thesaurus, was applied to perform a network analysis based on hypernyms, hyponyms, and synonyms relations linked to uncertainty words. The semantic and lexical relationships of uncertainty words were structurally identified. As a result, we identified the possibility of automatically expanding uncertainty words.

KEYWORDS

Text Mining, Bibliometrics, Uncertainty, Word2Vec, WordNet, Network Analysis

Citation status

* References for papers published after 2023 are currently being built.

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Journal of the Korean Society for Library and Information Science 2023 KCI Impact Factor : 0.84

Network Analysis between Uncertainty Words based on Word2Vec and WordNet

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* References for papers published after 2023 are currently being built.

Journal of the Korean Society for Library and Information Science 2023 KCI Impact Factor : 0.84

Network Analysis between Uncertainty Words based on Word2Vec and WordNet

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KEYWORDS

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