Extended VSM for XML Document Classification Using Frequent Subtrees

被引：0

作者：

Yang, Jianwu ^{[1
]}

Wang, Songlin ^{[1
]}

机构：

[1] Peking Univ, Inst Comp Sci & Tech, Beijing 100871, Peoples R China

来源：

FOCUSED RETRIEVAL AND EVALUATION | 2010年 / 6203卷

关键词：

XML Document; Classification; Vector Space Model (VSM); Structured Link Vector Model (SLVM); Frequent Subtree;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Structured link vector model (SLVM) is a representation proposed for modeling XML documents which was extended from the conventional vector space model (VSM) by incorporating document structures In this paper we describe the classification approach for XML documents based on SLVM in the Document Mining Challenge of INEX 2009 where the closed frequent subtrees as structural units are used for content extraction from the XML document and the Chi-square test is used for feature selection

引用

页码：441 / 448

页数：8

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