Clustering with Random Indexing K-tree and XML Structure

被引：0
|
作者：
De Vries, Christopher M. [1 ]
Geva, Shlomo [1 ]
De Vine, Lance [1 ]
机构：
[1] Queensland Univ Technol, Fac Sci & Technol, Brisbane, Qld 4001, Australia
来源：
FOCUSED RETRIEVAL AND EVALUATION | 2010年 / 6203卷
关键词：
INEX; XML; Mining; Documents; Clustering; Structure; K-tree; Random Indexing; Random Projection; LINDENSTRAUSS; JOHNSON;
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：
This paper describes the approach taken to the clustering task at INEX 2009 by a group at the Queensland University of Technology The Random Indexing (RI) K-tree has been used with a representation that is based on the semantic markup available in the INEX 2009 Wikipedia collection The RI K-tree is a scalable approach to clustering large document collections This approach has produced quality clustering when evaluated using two different methodologies
引用
收藏
页码：407 / 415
页数：9
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