• Title/Summary/Keyword: 역의 연관성 규칙

Search Result 5, Processing Time 0.024 seconds

Development of association rule threshold by balancing of relative rule accuracy (상대적 규칙 정확도의 균형화에 의한 연관성 측도의 개발)

  • Park, Hee Chang
    • Journal of the Korean Data and Information Science Society
    • /
    • v.25 no.6
    • /
    • pp.1345-1352
    • /
    • 2014
  • Data mining is the representative methodology to obtain meaningful information in the era of big data.By Wikipedia, association rule learning is a popular and well researched method for discovering interesting relationship between itemsets in large databases using association thresholds. It is intended to identify strong rules discovered in databases using different interestingness measures. Unlike general association rule, inverse association rule mining finds the rules that a special item does not occur if an item does not occur. If two types of association rule can be simultaneously considered, we can obtain the marketing information for some related products as well as the information of specific product marketing. In this paper, we propose a balanced attributable relative accuracy applicable to these association rule techniques, and then check the three conditions of interestingness measures by Piatetsky-Shapiro (1991). The comparative studies with rule accuracy, relative accuracy, attributable relative accuracy, and balanced attributable relative accuracy are shown by numerical example. The results show that balanced attributable relative accuracy is better than any other accuracy measures.

Proposition of balanced comparative confidence considering all available diagnostic tools (모든 가능한 진단도구를 활용한 균형비교신뢰도의 제안)

  • Park, Hee Chang
    • Journal of the Korean Data and Information Science Society
    • /
    • v.26 no.3
    • /
    • pp.611-618
    • /
    • 2015
  • By Wikipedia, big data is a broad term for data sets so large or complex that traditional data processing applications are inadequate. Data mining is the computational process of discovering patterns in huge data sets involving methods at the intersection of association rule, decision tree, clustering, artificial intelligence, machine learning. Association rule is a well researched method for discovering interesting relationships between itemsets in huge databases and has been applied in various fields. There are positive, negative, and inverse association rules according to the direction of association. If you want to set the evaluation criteria of association rule, it may be desirable to consider three types of association rules at the same time. To this end, we proposed a balanced comparative confidence considering sensitivity, specificity, false positive, and false negative, checked the conditions for association threshold by Piatetsky-Shapiro, and compared it with comparative confidence and inversely comparative confidence through a few experiments.

A study on the relatively causal strength measures in a viewpoint of interestingness measure (흥미도 측도 관점에서 상대적 인과 강도의 고찰)

  • Park, Hee Chang
    • Journal of the Korean Data and Information Science Society
    • /
    • v.28 no.1
    • /
    • pp.49-56
    • /
    • 2017
  • Among the techniques for analyzing big data, the association rule mining is a technique for searching for relationship between some items using various relevance evaluation criteria. This associative rule scheme is based on the direction of rule creation, and there are positive, negative, and inverse association rules. The purpose of this paper is to investigate the applicability of various types of relatively causal strength measures to the types of association rules from the point of view of interestingness measure. We also clarify the relationship between various types of confidence measures. As a result, if the rate of occurrence of the posterior item is more than 0.5, the first measure ($RCS_{IJ1}$) proposed by Good (1961) is more preferable to the first measure ($RCS_{LR1}$) proposed by Lewis (1986) because the variation of the value is larger than that of $RCS_{LR1}$, and if the ratio is less than 0.5, $RCS_{LR1}$ is more preferable to $RCS_{IJ1}$.

무국경시대(無國境時代)의 국가경제(國家經濟) 속성(屬性)과 정부(政府)의 역할(役割)

  • Yu, Jeong-Ho
    • KDI Journal of Economic Policy
    • /
    • v.17 no.4
    • /
    • pp.3-61
    • /
    • 1995
  • 기업활동의 범세계화(汎世界化), WTO 출범 등으로 세계경제(世界經濟)의 통합(統合)과 무국경화(無國境化)가 진행되고 있다. 이에 따라 자본 고급인력 등 국제이동성(國際移動性)이 높은 자원들이 유동화(流動化)할 것이고, 그 결과 토지, 사회간접자본, 미숙련 노동력, '경기규칙', 사회 전반적인 과학기술수준, 문화 등 국제이동성(國際移動性)이 낮은 광의(廣義)의 생산요소(生産要素)들이 한 나라의 경제적 특성을 결정하고 경제 기반을 이룰 것이다. 무국경시대(無國境時代)에는 자원배분뿐 아니라 자원유치(資源幽致)가 한 나라의 경제성과에 큰 영향을 미칠 것이며, 따라서 자원유치가 경제운영의 중요한 과제로 등장할 것으로 예상된다. 자원의 국제적(國際的) 유동화(流動化)는 국제이동성(國際移動性)이 높은 생산요소들이 국제이동성이 낮은 생산요소들을 찾아 경제활동의 근거지를 선택하는 것이므로, 무국경시대(無國境時代)에는 저이동성(低移動性) 생산요소(生産要素)들의 양적(量的) 확충(擴充)및 질적(質的) 수준(水準) 제고(提高)를 통한 자원유치(資源誘致)의 가능성이 커지며, 따라서 일부 첨단기술산업의 육성보다는 전반적인 과학기술(科學技術) 수준(水準) 제고(提高)가, 소수의 고급인력 확보보다는 다수(多數) 미숙련(未熟練) 인력(人力)의 질적(質的) 수준(水準) 제고(提高)가 경제성과를 높이는 데 상대적으로 더 중요해진다. 또한 경제적(經濟的) 무국경화(無國境化)는 국적에 관한 속인주의(屬人主義)의 퇴조와 속지주의(屬地主義)의 보편화, 한 나라 국경 안에 상이한 특성을 가진 지방경제(地方經濟)들의 부상, 국내 산업들 사이의 산업연관관계(産業聯關關係) 약화(弱化) 등의 변화를 수반할 것으로 예상된다. 이같은 변화로 개방주의(開放主義) 및 무차별주의(無差別主義)의 확대(擴大)가 불가피하게 되고 특정 산업에 대한 정부지원 및 보호의 근거가 약화되는 반면, 자원배분의 참고단위로서 개별(個別) 경제주체(經濟主體)들의 중요성이 높아지며 그만큼 시장경쟁을 지배하는 '경기규칙(鏡技規則)'의 올바른 정립이 중요해진다. 그러므로 정부는 자원배분에 대한 개업을 축소하고, 저이동성(低移動性) 생산요소(生産要素)들의 양적 질적 수준 제고, 특히 '경기규칙(競技規則)'의 공정성(公正性) 및 투명성(透明性)을 높여야 한다. 즉 정부가 폐쇄성 높은 경제의 지배인으로부터 개방(開放)된 시장경제(市場經濟)의 후견인으로 바뀌어야 한다. 이것이, 시장질서(市場秩序)가 우리를 먹여 살리는 손이라는 인식이나 국제분업(國際分業)이 살 길이라는 확신이 부족한 우리 사회에 무국경시대(無國境時代)가 던지는 어려운 도전(挑戰)이다.

  • PDF

Automatic Recommendation of Panel Pool Using a Probabilistic Ontology and Researcher Networks (확률적 온톨로지와 연구자 네트워크를 이용한 심사자 자동 추천에 관한 연구)

  • Lee, Jung-Yeoun;Lee, Jae-Yun;Kang, In-Su;Shin, Suk-Kyung;Jung, Han-Min
    • Journal of the Korean Society for information Management
    • /
    • v.24 no.3
    • /
    • pp.43-65
    • /
    • 2007
  • Automatic recommendation system of panel pool should be designed to support universal, expertness, fairness, and reasonableness in the process of review of proposals. In this research, we apply the theory of probabilistic ontology to measure relatedness between terms in the classification of academic domain, enlarge the number of review candidates, and rank recommendable reviewers according to their expertness. In addition, we construct a researcher network connecting among researchers according to their various relationships like mentor, coauthor, and cooperative research. We use the researcher network to exclude inappropriate reviewers and support fairness of reviewer recommendation process. Our methodology recommending proper reviewers is verified from experts in the field of proposal examination. It propose the proper method for developing a resonable reviewer recommendation system.