By Xudong Luo, Jeffrey Xu Yu, Zhi Li
This e-book constitutes the court cases of the tenth overseas convention on complicated information Mining and purposes, ADMA 2014, held in Guilin, China in the course of December 2014. The forty eight commonplace papers and 10 workshop papers provided during this quantity have been conscientiously reviewed and chosen from ninety submissions. They take care of the subsequent subject matters: info mining, social community and social media, suggest structures, database, dimensionality relief, improve laptop studying concepts, type, colossal information and functions, clustering equipment, laptop studying, and information mining and database.
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Additional info for Advanced Data Mining and Applications: 10th International Conference, ADMA 2014, Guilin, China, December 19-21, 2014. Proceedings
G. high proﬁt), that is High Utility Itemsets (HUIs). HUIM has a wide range of applications such as cross-marketing and click stream analysis and biomedical applications [2,4,6,13]. The problem of HUIM is widely recognized as more difﬁcult than that of FIM. In FIM, the downward-closure property states that the support (frequency) of an itemset is anti-monotonic , that is the supersets of an infrequent itemset are infrequent. This property is very powerful to prune the search space. In HUIM, the utility of an itemset is neither monotonic or anti-monotonic.
PAKDD 2014, Part I. LNCS, vol. 8443, pp. 40–52. Springer, Heidelberg (2014) 6. : VMSP: Eﬃcient Vertical Mining of Maximal Sequential Patterns. , van Beek, P. ) Canadian AI. LNCS, vol. 8436, pp. 83–94. Springer, Heidelberg (2014) 7. : Novel Concise Representations of High Utility Itemsets using Generator Patterns. , Li, Z. ) ADMA 2014. LNCS, vol. 8933, pp. 30–43. Springer, Heidelberg (2014) 8. : Isolated items discarding strategy for discovering high utility itemsets. Data & Knowledge Engineering 64(1), 198–217 (2008) 9.
In: 19th International Conference on Geoinformatics, pp. 1–5. IEEE Computer Society, Shanghai (2011) 17. : An improved matrix sorting index association rule data mining algorithm. In: 33rd Chinese Control Conference, pp. 500–505. IEEE Computer Society, Nanjing (2014) 18. : MapReduce as a programming model for association rules algorithm on Hadoop. In: 3rd International Conference on Information Sciences and Interaction Sciences, pp. 99–102. IEEE Computer Society, Chengdu (2010) 19. : Research of Massive Web Log Data Mining Based on Cloud Computing.
Advanced Data Mining and Applications: 10th International Conference, ADMA 2014, Guilin, China, December 19-21, 2014. Proceedings by Xudong Luo, Jeffrey Xu Yu, Zhi Li