Titlebook: Knowledge Discovery in Inductive Databases; Third International Bart Goethals,Arno Siebes Conference proceedings 2005 Springer-Verlag Berl

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書目名稱Knowledge Discovery in Inductive Databases影響因子(影響力)




書目名稱Knowledge Discovery in Inductive Databases影響因子(影響力)學(xué)科排名




書目名稱Knowledge Discovery in Inductive Databases網(wǎng)絡(luò)公開度




書目名稱Knowledge Discovery in Inductive Databases網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Knowledge Discovery in Inductive Databases被引頻次




書目名稱Knowledge Discovery in Inductive Databases被引頻次學(xué)科排名




書目名稱Knowledge Discovery in Inductive Databases年度引用




書目名稱Knowledge Discovery in Inductive Databases年度引用學(xué)科排名




書目名稱Knowledge Discovery in Inductive Databases讀者反饋




書目名稱Knowledge Discovery in Inductive Databases讀者反饋學(xué)科排名

暗語

GOAT

facilitate

ADAGE

Taneli Mielik?inen view... It extract long timescale macroscopic/mesoscopic dynamics from microscopic equations in an intuitively understandable way rather than in a mathematically rigorous manner and introduces readers to a mathematically elementary, but useful and widely applicable technique for analyzing asymptoti

茁壯成長

Arnaud Soulet,Bruno Crémilleux,Fran?ois Rioulttents a priori and clearly.This book presents a comprehensive account of the ?renormalization-group (RG) method and its extension, the doublet scheme, in a geometrical point of view... It extract long timescale macroscopic/mesoscopic dynamics from microscopic equations in an intuitively understandab

myalgia

view... It extract long timescale macroscopic/mesoscopic dynamics from microscopic equations in an intuitively understandable way rather than in a mathematically rigorous manner and introduces readers to a mathematically elementary, but useful and widely applicable technique for analyzing asymptoti

Acclaim

Models and Indices for Integrating Unstructured Data with a Relational Database integration of semi-structured sources with existing structured databases for seamless querying. This integration requires extracting structured column values from the unstructured source and mapping them to known database entities. Existing methods of data integration do not effectively exploit th

reperfusion

Constraint Relaxations for Discovering Unknown Sequential Patternsthe solution commonly accepted – the use of constraints – approximates the mining process to a verification of what are the frequent patterns among the specified ones, instead of the discovery of unknown and unexpected patterns..In this paper, we propose a new methodology to mine sequential patterns

夜晚

Mining Formal Concepts with a Bounded Number of Exceptions from Transactional Dataated to sets of attributes or items). A typical important case concerns formal concept mining (i.e., maximal rectangles of true values or associated closed sets by means of the so-called Galois connection). It has been applied with some success to, e.g., gene expression data analysis where objects d