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학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
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연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국자료분석학회 Journal of The Korean Data Analysis Society Journal of The Korean Data Analysis Society 제15권 제4호
- 발행연도
- 2013.1
- 수록면
- 1,723 - 1,731 (9page)
이용수
초록· 키워드
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Data mining is the process of sorting through a massive volume database and discovering useful information. One of the well-studied problems in data mining is association rule technique. An association rule technique finds the relation among itemsets in a big database. Some interestingness measures have been developed in association rule mining. Such interestingness measures are divided into objective, subjective, and semantic measures. In this paper we investigated the relationship between symmetric confirmation measures and association thresholds, and checked the conditions of interestingness measures by Piatetsky-Shapiro. And then we inquired into the some properties for these measure. The comparative studies with support, confidence, and lift were shown by numerical examples. As a result, we found that symmetric confirmation measures is better than support, confidence, and lift because these measures have the direction of the association.
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등록된 정보가 없습니다.
참고문헌 (31)
참고문헌 신청
Saygin, Y. / 2002 / Using unknowns to prevent discovery of association rules / Proceedings of 2002 Conference on Research Issues in Data Engineering :45~54
Tan, P. / 2004 / Selecting the right objective measure for association analysis / Information Systems 29:293~313
Toivonen, H. / 1996 / Sampling large database for association rules / Proceedings of the 22nd VLDB Conference :134~145
Agrawal, R. / 1993 / Mining association rules between sets of items in large databases / Proceedings of the ACM SIGMOD Conference on Management of Data : 207 ~ 216
Agrawal, R. / 1994 / Fast algorithms for mining association rules / Proceedings of the 20th VLDB Conference : 487 ~ 499
Tan, P. / 2004 / Selecting the right objective measure for association analysis / Information Systems 29:293~313
Toivonen, H. / 1996 / Sampling large database for association rules / Proceedings of the 22nd VLDB Conference :134~145
Agrawal, R. / 1993 / Mining association rules between sets of items in large databases / Proceedings of the ACM SIGMOD Conference on Management of Data : 207 ~ 216
Agrawal, R. / 1994 / Fast algorithms for mining association rules / Proceedings of the 20th VLDB Conference : 487 ~ 499
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