Titlebook: Net Gain; Profit im Netz John Hagel,Arthur G. Armstrong Book 1999 Springer Fachmedien Wiesbaden 1999 Erfolg.Management.Markt.Marktpositioni

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solution..As dimensionality increases, the number of defined regions must increase, but the memory required for the exclusion calculation does not. We show that the technique gives excellent performance over the SISAP benchmark data sets, and most interestingly we show how increases in dimensionali

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John Hagel III,Arthur G. Armstrong solution..As dimensionality increases, the number of defined regions must increase, but the memory required for the exclusion calculation does not. We show that the technique gives excellent performance over the SISAP benchmark data sets, and most interestingly we show how increases in dimensionali

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John Hagel III,Arthur G. Armstrongtions. Over time the datasets being searched have become more complex, leading to higher dimensional spaces. It is now understood that even an approximate search in a very high-dimensional space is destined to require . time and space..Almost entirely missing from the research literature however is

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e such searching and discuss its advantages concerning similarity quantifications, namely its efficiency and robustness. We also propose a pioneering implementation of the relational similarity search for the Euclidean spaces and report its extreme filtering power in comparison with 3 contemporary t

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r, computing the .-nearest neighbor sets for all points in a database is expensive in terms of computational costs. Therefore, specific index structures have been invented to apply pruning heuristics which aim at reducing the search space. At time, the state-of-the-art index structure for enabling f

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