A frequent itemset mining algorithm based on the Principle of Inclusion-Exclusion and transaction mapping
作者： Ke-Chung Lin , I-En Liao , Tsui-Ping Chang , Shu-Fan Lin
DOI: 10.1016/J.INS.2014.02.060
关键词: Data mining 、 Correctness 、 Mathematics 、 A priori and a posteriori 、 Set theory 、 Data mining algorithm 、 Property (programming) 、 Database transaction 、 Process (computing) 、 Counting process
摘要: … We first discuss the background of the Principle of Inclusion and Exclusion in Section 3.1 … , we present how the interval list assists counting with the Principle of Inclusion–Exclusion. …
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sci-hub.se 参考文章(22)
Dao-I Lin, Zvi M. Kedem, Pincer-Search: A New Algorithm for Discovering the Maximum Frequent Set extending database technology. pp. 105- 119 ,(1998) , 10.1007/BFB0100980
Srinivasan Parthasarathy, Mitsunori Ogihara, Mohammed J Zaki, Wei Li, New algorithms for fast discovery of association rules knowledge discovery and data mining. pp. 283- 286 ,(1997)
Ramakrishnan Srikant, Rakesh Agrawal, Fast Algorithms for Mining Association Rules in Large Databases very large data bases. pp. 487- 499 ,(1994)
Walter A. Kosters, Wim Pijls, Viara Popova, Complexity analysis of depth first and FP-growth implementations of APRIORI machine learning and data mining in pattern recognition. pp. 284- 292 ,(2003) , 10.1007/3-540-45065-3_25
Yuh-Jiuan Tsay, Tain-Jung Hsu, Jing-Rung Yu, FIUT: A new method for mining frequent itemsets Information Sciences. ,vol. 179, pp. 1724- 1737 ,(2009) , 10.1016/J.INS.2009.01.010
Elena Baralis, Luca Cagliero, Tania Cerquitelli, Paolo Garza, Generalized association rule mining with constraints Information Sciences. ,vol. 194, pp. 68- 84 ,(2012) , 10.1016/J.INS.2011.05.016
Dao-I Lin, Z.M. Kedem, Pincer-search: an efficient algorithm for discovering the maximum frequent set IEEE Transactions on Knowledge and Data Engineering. ,vol. 14, pp. 553- 566 ,(2002) , 10.1109/TKDE.2002.1000342
Sergey Brin, Rajeev Motwani, Jeffrey D. Ullman, Shalom Tsur, Dynamic itemset counting and implication rules for market basket data international conference on management of data. ,vol. 26, pp. 255- 264 ,(1997) , 10.1145/253260.253325
Kuen-Fang Jea, Ming-Yuan Chang, Ke-Chung Lin, An efficient and flexible algorithm for online mining of large itemsets Information Processing Letters. ,vol. 92, pp. 311- 316 ,(2004) , 10.1016/J.IPL.2004.09.008
Jiawei Han, Jian Pei, Yiwen Yin, Mining frequent patterns without candidate generation international conference on management of data. ,vol. 29, pp. 1- 12 ,(2000) , 10.1145/335191.335372