Automatic Keyword Extraction using Hierarchical Graph Model Based on Word Co-occurrences 


Vol. 44,  No. 5, pp. 522-536, May  2017


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  Abstract

Keyword extraction can be utilized in text mining of massive documents for efficient extraction of subject or related words from the document. In this study, we proposed a hierarchical graph model based on the co-occurrence relationship, the intrinsic dependency relationship between words, and common sub-word in a single document. In addition, the enhanced TextRank algorithm that can reflect the influences of outgoing edges as well as those of incoming edges is proposed. Subsequently a novel keyword extraction scheme using the proposed hierarchical graph model and the enhanced TextRank algorithm is proposed to extract representative keywords from a single document. In the experiments, various evaluation methods were applied to the various subject documents in order to verify the accuracy and adaptability of the proposed scheme. As the results, the proposed scheme showed better performance than the previous schemes.


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  Cite this article

[IEEE Style]

K. Song and Y. Kim, "Automatic Keyword Extraction using Hierarchical Graph Model Based on Word Co-occurrences," Journal of KIISE, JOK, vol. 44, no. 5, pp. 522-536, 2017. DOI: .


[ACM Style]

KwangHo Song and Yoo-Sung Kim. 2017. Automatic Keyword Extraction using Hierarchical Graph Model Based on Word Co-occurrences. Journal of KIISE, JOK, 44, 5, (2017), 522-536. DOI: .


[KCI Style]

송광호, 김유성, "단어 동시출현관계로 구축한 계층적 그래프 모델을 활용한 자동 키워드 추출 방법," 한국정보과학회 논문지, 제44권, 제5호, 522~536쪽, 2017. DOI: .


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