Mining association rules in interval-based temporal sequences
A new algorithm was proposed to find association rules in interval-based sequences, which was based on the concept of interval time series and used the properties of frequent closed patterns.
ZHU Tian1 +3 more
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OmicsARules: a R package for integration of multi-omics datasets via association rules mining. [PDF]
Chen D, Zhang F, Zhao Q, Xu J.
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Investigation of multimorbidity patterns and association rules in patients with type 2 diabetes mellitus using association rules mining algorithm. [PDF]
Liu L, Wang X, Gui M, Ju F, Cao L, Bi B.
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Health promotion campaigns using social media: association rules mining and co-occurrence network analysis of Twitter hashtags. [PDF]
Ghahramani A +2 more
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In this paper, we address the problem of generating relevant rare association rules. In the literature, this problem has not yet been studied in detail, although rare association rules can also contain important information just as frequent association rules do. Our work is motivated by the long-standing open question of devising an efficient algorithm
Szathmary, Laszlo +2 more
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Negative and positive association rules mining from text using frequent and infrequent itemsets. [PDF]
Mahmood S, Shahbaz M, Guergachi A.
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Data mining technique for identifying mortality patterns in a pulmonary tuberculosis cohort. [PDF]
Rocha MS +4 more
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An integrated analysis method for critical human factors and paths in hazardous chemical storage accidents based on association rule mining and bayesian networks. [PDF]
Ma S, Jiang W.
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Multi-level screening method for network security alarms based on DBSCAN algorithm and rete rule inference. [PDF]
Ni L, Zhang S, Huang K, Wang Y.
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Application of improved FP-tree algorithm in rural accurate information service. [PDF]
Jin Y, Zhao J, Li X, Wu J.
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