단어 간 의미적 연관성을 고려한 개선된 문서 요약 방법 연구

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자동 문서요약 단어 그룹화 텍스트랭크
Along with the recent development and distribution of smart devices, data contained in documents appearing on the internet are increasing exponentially. As documents are increasing exponentially, only the titles and main points are shown to users as a solution to figure out information in a document they want. Only with brief contents, however, users may find it difficult to get the information of a document they want. If document wanted by a user is expressed in an accurate form, it will be helpful when trying to find out necessary information.
Document summarization is referred to eliminating redundancies and producing condensed information while maintaining consistency in collected documents. Automatic document summarization technology is to process a large amount of documents automatically and efficiently by extracting main sentences from a document using a computer and eliminating overlapped contents.
To summarize a document efficiently, the present study uses a text rank algorithm. The text rank algorithm expresses sentences or keywords as a graph and employs the peaks or main lines of a graph to figure out semantic correlation between words and sentences and understand the importance of sentences. Through this, it goes through a process to extract the superordinate keywords of sentences and extract main sentences based on those keywords. To go through a process to extract main sentence s, word grouping is done. For word grouping, a particular weighting scale is used to screen sentences having a high weighted value. Based on the screen sentences, main sentences are extracted, and the document is summarized. This study has proven that it shows higher performance than any of the document summarization methods previously examined and performs summarization more efficiently.
Alternative Title
An Improved Automatic Text Summarization Using Semantical word relatedness
Alternative Author(s)
JunSeok Cha
조선대학교 산업기술융합대학원
산업기술융합대학원 소프트웨어융합공학과
Awarded Date
2017. 2
Table Of Contents
Ⅰ. 서 론 1
A. 연구 배경 및 목적 1
B. 연구 내용 및 구성 3

Ⅱ. 관련 연구 4
A. 생성 요약 기법 4
B. 추출 요약 기법 7

Ⅲ. 단어 간 연관성을 고려한 문서요약 방법 11
A. 시스템 구성도 11
B. 대표 키워드 추출 12
1. 전처리 과정 12
a. 토큰화(Tokenizing) 12
b. 불용어 제거(Stopword) 13
c. 어간 추출(Stemming) 14
d. 품사 판별(part-of-speech tagging) 14
e. 키워드 추출(Keyword Extraction) 16
2. 간선 그래프 모델링 16
3. 텍스트 랭크를 이용한 대표 키워드 추출 18
C. 단어 간 연관성을 고려한 중요 문장 추출 22
1. 단어 그룹화 22
2. 문서 요약 25

Ⅳ. 실험 및 결과 30
A. 데이터 세트(Data Set) 30
1. TAC(Text Analysis Conference) 30
B. 실험 평가 방법 및 결과 분석 31
1. 실험 평가 방법 31
2. 결과 분석 32
a. 강한 문장 가중치 점수를 이용한 결과 분석 32
b. 비교 평가 실험 35

Ⅴ. 결론 및 제언 39

참고문헌 40
조선대학교 산업기술융합대학원
차준석. (2016). 단어 간 의미적 연관성을 고려한 개선된 문서 요약 방법 연구
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Engineering > Theses(Master)(산업기술창업대학원)
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