Titlebook: Database and Expert Systems Applications; 27th International C Sven Hartmann,Hui Ma Conference proceedings 2016 Springer International Publ

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Prospects of the further development of EISe existing HC algorithms focus on either the quality of the dendrogram or the ability of mining arbitrary shaped clusters. To address the above two aspects simultaneously, we present HICMEN by adopting (1) the classic agglomerative clustering framework that can generate a complete dendrogram, and (2

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Thomas Reichmann,Alfred Vo?schulte novel framework that permits us to detect hierarchical outliers in a consistent manner, providing a desired monotonicity property, which implies that a data observation that finds enough support so as to be disregarded as an outlier at a level of the hierarchy, will not be labelled as an outlier wh

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https://doi.org/10.1007/978-3-319-44403-1data mining; linked open data; mobile ad hoc networks; natural language processing; semantic Web; context

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軍械庫

Database and Expert Systems Applications978-3-319-44403-1Series ISSN 0302-9743 Series E-ISSN 1611-3349

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General Purpose Index-Based Method for Efficient MaxRS Queryed to solve the .-enclosing problem in time .(1) for any given . value if indexes are sorted according to the optimizing criteria, or . without using any index, which is comparative to the current most efficient work.