• 제목/요약/키워드: weights(priority vector)

검색결과 3건 처리시간 0.02초

AHP를 이용한 대학수학 성취도 요인의 중요도 추정 (On Estimation of Weights for Elementary Mathematics Achievement Factors by Using AHP)

  • 함형범
    • 한국수학사학회지
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    • 제20권3호
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    • pp.91-104
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    • 2007
  • 본 연구에서는 대학수학 교육을 향상시키기 위한 참조 지표를 얻기 위하여 AHP를 이용하여 대학수학 성취도 요인의 상대적 중요도를 추정하는 방법을 연구하였다. 이를 위하여 AHP의 개요 및 역사를 고찰하고 설문조사에 의해 얻은 자료를 통해 쌍대비교행렬을 작성하고 고유벡터방법으로 중요도를 추정하였다.

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전문가 설문에 의한 AHP 가중치 산출의 적용한계에 관한 연구 (A Study on application limitation of AHP priority vector with Expert measurement)

  • 김웅이;김도현;최연철
    • 한국항공운항학회지
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    • 제18권3호
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    • pp.92-98
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    • 2010
  • The AHP methodology compares criteria, or alternatives with respect to a criterion, in a natural, pairwise mode. AHP has been applied in a wide variety of applications multi objective decision making being just one. If a group of expert with different aspect, they need some way to revise expert group. We proposed the concatenation of expert to survey the AHP pairwise question for multi-attribute decision making. In this paper, we suggest a way to revise the expert's priorities in hierarch using concept of different group opinion.

SNS대상의 지능형 자연어 수집, 처리 시스템 구현을 통한 한국형 감성사전 구축에 관한 연구 (Research on Designing Korean Emotional Dictionary using Intelligent Natural Language Crawling System in SNS)

  • 이종화
    • 한국정보시스템학회지:정보시스템연구
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    • 제29권3호
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    • pp.237-251
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    • 2020
  • Purpose The research was studied the hierarchical Hangul emotion index by organizing all the emotions which SNS users are thinking. As a preliminary study by the researcher, the English-based Plutchick (1980)'s emotional standard was reinterpreted in Korean, and a hashtag with implicit meaning on SNS was studied. To build a multidimensional emotion dictionary and classify three-dimensional emotions, an emotion seed was selected for the composition of seven emotion sets, and an emotion word dictionary was constructed by collecting SNS hashtags derived from each emotion seed. We also want to explore the priority of each Hangul emotion index. Design/methodology/approach In the process of transforming the matrix through the vector process of words constituting the sentence, weights were extracted using TF-IDF (Term Frequency Inverse Document Frequency), and the dimension reduction technique of the matrix in the emotion set was NMF (Nonnegative Matrix Factorization) algorithm. The emotional dimension was solved by using the characteristic value of the emotional word. The cosine distance algorithm was used to measure the distance between vectors by measuring the similarity of emotion words in the emotion set. Findings Customer needs analysis is a force to read changes in emotions, and Korean emotion word research is the customer's needs. In addition, the ranking of the emotion words within the emotion set will be a special criterion for reading the depth of the emotion. The sentiment index study of this research believes that by providing companies with effective information for emotional marketing, new business opportunities will be expanded and valued. In addition, if the emotion dictionary is eventually connected to the emotional DNA of the product, it will be possible to define the "emotional DNA", which is a set of emotions that the product should have.