Titlebook: Knowledge Discovery from XML Documents; First International Richi Nayak,Mohammed J. Zaki Conference proceedings 2006 Springer-Verlag Berli

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书目名称Knowledge Discovery from XML Documents影响因子(影响力)学科排名




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书目名称Knowledge Discovery from XML Documents被引频次学科排名




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书目名称Knowledge Discovery from XML Documents年度引用学科排名




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书目名称Knowledge Discovery from XML Documents读者反馈学科排名

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Tok Wang Ling, called leaves, which pile up locally like pages of a book. The theory of foliations, as it is known, began with the work of C. Ehresmann and G. Reeb, in the 1940‘s; however, as Reeb has himself observed, already in the last century P. Painleve saw the necessity of creating a geometric theory (of f

chastise

Laura Irina Rusu,Wenny Rahayu,David Taniars special focus, of course, on the generalized pseudo-Riemannian geometry of Section 3.2.5—to the theory of general relativity. We shall begin with a general introduction into our theme in Section 5.1, where we also introduce our notational conventions concerning general relativity. Section 5.2 is d

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Duodenitis

Marko Brunzel,Myra Spiliopoulou in high-dimensional time-series data (e.g., video sequence classification and clustering). In the first part of the paper, we provide a rather extensive review of some existing approaches to defining distances on spaces of stochastic processes. The majority of these distances are, in one way or ano

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Atakan Kurt,Engin Tozal in high-dimensional time-series data (e.g., video sequence classification and clustering). In the first part of the paper, we provide a rather extensive review of some existing approaches to defining distances on spaces of stochastic processes. The majority of these distances are, in one way or ano

垄断

Capturing Semantics in XML Documents effective management of structured data. The semantics that can be expressed in the ER data model include the representation of entity types together with their identifiers and attributes, n-ary relationship types together with their participating entity types and attributes, and functional depende

capsule

archenemy

XML Document Clustering by Independent Component Analysise meanwhile find the underlying latent variables of XML structures to improve the quality of the clustering. This paper proposes a novel strategy to cluster XML documents based on ICA. According to . extracted from XML trees, the document was at first represented as Vector Space Model (VSM).Then ICA

Irritate

Discovering Multi Terms and Co-hyponymy from XHTML Documents with XTREEMcome the knowledge acquisition bottleneck. The identification of concepts and relations with only minimal user interaction is still a challenging objective. Current approaches performed to extract semantics often use association rules or clustering upon regular flat text. In this paper we describe a