Earticle

초록

영어

The increasing interests on patents have led many individuals and companies to apply for many patents in various areas. Applied patents are stored in the forms of electronic documents. The search and categorization for these documents are issues of major fields in data mining. Especially, the keyword extraction by which we retrieve the representative keywords is important. Most of techniques for it is based on vector space model. But this model is simply based on frequency of terms in documents, gives them weights based on their frequency and selects the keywords according to the order of weights. However, this model has the limit that it cannot reflect the relations between keywords. This paper proposes the advanced way to extract the more representative keywords by overcoming this limit. In this way, the proposed model firstly prepares the candidate set using the vector model, then makes the graph which represents the relation in the pair of candidate keywords in the set and selects the keywords based on this relationship graph.

목차

1.서 론
 2 관련연구
  2.1 텍스트 마이닝
  2.2 벡터 공간 모델
  2.3 그래프 기반 모델
 3. 관계성 그래프 모델
  3.1 후보 키워드군 추출
  3.2 섹션별 후보 키워드군의 문장 내위치 정보 추출
  3.3 관계성 기반 인접행렬
  3.4 간선 제거에 의한 키워드 추출
 4. 실험 및 평가
 5. 결론
 6. References

키워드

저자

• 이순근 [ Soon Geun Lee | 강릉대학교 산업경영공학과 ]
• 임영문 [ Young Moon Leem | 강릉대학교 산업경영공학과 ] Corresponding Author
• 엄완섭 [ Wan Sup Um | 강릉대학교 산업경영공학과 ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  대한안전경영과학회지 [Journal of Korea Safety Management & Science]

• 간기

  계간

• pISSN

  1229-6783

• eISSN

  2288-1484

• 수록기간

  1999~2025

• 십진분류

  KDC 530 DDC 620