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Source apportionment of potentially toxic elements (PTEs) in soils of the Huayuan Manganese Mining Area using PCA-IDW and PMF. [PDF]

Sci Rep
Zheng F, Ren B, Deng X, Zhang S, Zhou B, Li R, Luo R.   +6 more
europepmc   +1 more source

Integrating ecological and anthropogenic risk identifies emerging Ebola spillover hotspots

Moir M, Tegally H, Moges DM, Dor G, Poongavanan J, Baxter C, Lessells RJ, Kraemer MU, Judge C, Gutierrez B, Ebengo DM, Kinganda-Lusamaki E, Mbala-Kingebeni P, Muyembe-Tamfum J, Nachega JB, de Oliveira T, Mavian CN.   +16 more
europepmc   +1 more source

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Mining Condensed Frequent-Pattern Bases

Knowledge and Information Systems, 2004
Frequent-pattern mining has been studied extensively and has many useful applications. However, frequent-pattern mining often generates too many patterns to be truly efficient or effective. In many applications, it is sufficient to generate and examine frequent patterns with a sufficiently good approximation of the support frequency instead of in full ...
Jian Pei, Guozhu Dong, Jiawei Han
exaly   +3 more sources

Approximate mining of frequent patterns on streams [PDF]

Intelligent Data Analysis, 2007
Many critical applications, like intrusion detection or stock market analysis, require a nearly immediate result based on a continuous and infinite stream of data. In most cases finding an exact solution is not compatible with limited availability of resources and real time constraints, but an approximation of the exact result is enough for most ...
SILVESTRI, Claudio, ORLANDO, Salvatore
openaire   +5 more sources

Mining frequent trajectory pattern based on vague space partition

Knowledge-Based Systems, 2013
Frequent trajectory pattern mining is an important spatiotemporal data mining problem with broad applications. However, it is also a difficult problem due to the approximate nature of spatial trajectory locations.
Xiaohui Yan, Kunyuan Hu
exaly   +1 more source

Mining frequent patterns with the pattern tree

New Generation Computing, 2005
Mining frequent patterns with a frequent pattern tree (FP-tree in short) avoids costly candidate generation and repeatedly occurrence frequency checking against the support threshold. It therefore achieves much better performance and efficiency than Apriori-like algorithms. However, the database still needs to be scanned twice to get the FP-tree.
Hao Huang, Xindong Wu 0001, Richard Relue   +2 more
openaire   +2 more sources