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An Improved Automatic Text Summarization Based on Lexical Chaining Using Semantical Word Relatedness
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단어 간 의미적 연관성을 고려한 어휘 체인 기반의 개선된 자동 문서요약 방법

논문 기본 정보

Type
Academic journal
Author
Journal
한국스마트미디어학회 스마트미디어저널 스마트미디어저널 제6권 제1호 KCI Accredited Journals
Published
2017.1
Pages
22 - 29 (8page)

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An Improved Automatic Text Summarization Based on Lexical Chaining Using Semantical Word Relatedness
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Research history (2)

2017

An Improved Automatic Text Summarization Based on Lexical Chaining Using Semantical Word Relatedness
JunSeokCha ,  김정인 ,  Pan Koo Kim 스마트미디어저널 2017.01 Academic journal

2016

An Improved Automatic Text Summarization Using Semantical word relatedness
차준석 소프트웨어융합공 2016.01 Thesis
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Abstract· Keywords

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Due to the rapid advancement and distribution of smart devices of late, document data on the Internet is on the sharp increase. The increment of information on the Web including a massive amount of documents makes it increasingly difficult for users to understand corresponding data. In order to efficiently summarize documents in the field of automated summary programs, various researches are under way. This study uses TextRank algorithm to efficiently summarize documents. TextRank algorithm expresses sentences or keywords in the form of a graph and understands the importance of sentences by using its vertices and edges to understand semantic relations between vocabulary and sentence. It extracts high-ranking keywords and based on keywords, it extracts important sentences. To extract important sentences, the algorithm first groups vocabulary. Grouping vocabulary is done using a scale of specific weight. The program sorts out sentences with higher scores on the weight scale, and based on selected sentences, it extracts important sentences to summarize the document. This study proved that this process confirmed an improved performance than summary methods shown in previous researches and that the algorithm can more efficiently summarize documents.
#텍스트 랭크 알고리즘 #문서 요약 #어휘 체인 #TextRank algorithm #ducument summary #Lexical Chain

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References (16)

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C. Y. Lin / 2004 / Automatic evaluation of su mmaries using n-gram co-occurrence statistics / Proceedings of Human Language Technology Conference (HLT-NAACL 2003) google schola Chanback Jeong / 2008 / A News Recommendation System based on Document Clustering Using WordNet / Department of Computer Science & Engineering Hangyang University google schola D. D. Lewis / 1996 / Natural language processing for information retrieval / Communications o f the ACM 39 (1) : 92 ~ 101 google schola E. D. Liddy / 1993 / DR-LINK’s : linguistic-comceptual approach to document and detection / The First Text REtreival Conference : 113 ~ 129 google schola Henning, Leonhard / 2009 / Topic-based Multi-Documen t Summarization with Probabilistic Latent Seman tic Analysis / Proceedings of the International Co nference RANLP'09 google schola

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