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6 篇文献
 
Hierarchical Clustering of Massive, High Dimensional Data Sets by Exploiting Ultrametric Embedding  
Coding of data, usually upstream of data analysis, has crucial impli- cations for the data analysis results. By modifying the data coding - through use of less than full precision in data values - we ......
Siam Journal on Scientific Computing  2008
6次引用 0 0
Clustering in Massive Data Sets  
We review the time and storage costs of search and clustering algorithms. We exemplify these, based on case-studies in astronomy, information retrieval, visual user interfaces, chemical databases, and......
Handbook of Massive Data Sets  1999
17次引用 0 0
Hierarchical clustering of massive, high dimensional data sets by exploiting ultrametric embedding  
Coding of data, usually upstream of data analysis, has crucial implications for the data analysis results. By modifying the data coding – through use of less than full precision in data values – we ca......
1次引用 0 0
A Polynomial-time Metric for Outerplanar Graphs  
Graphs are mathematical structures that are capable of representing relational data. In the chemoinformatics context, they have be- come very popular for the representation of molecules. However, a lo......
Mining and Learning with Graphs  2007
0次引用 0 0
RESEARCHER:  
First and foremost we would like to express our true and sincere thanks and gratitude to PM Dr Naomie Salim, for the guidance, support and encouragements during the course of this work. Also, we would......
0次引用 0 0
RASCAL: Calculation of Graph Similarity using Maximum Common Edge Subgraphs  
A new graph similarity calculation procedure is introduced for comparing labeled graphs. Given a minimum similarity threshold, the procedure consists of an initial screening process to determine wheth......
The Computer Journal  2002
50次引用 0 0

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