A New Measure of the Cluster Hypothesis

被引：0
|
作者：
Smucker, Mark D. [1 ]
Allan, James [2 ]
机构：
[1] Univ Waterloo, Dept Management Sci, Waterloo, ON N2L 3G1, Canada
[2] Univ Massachusetts Amherst, Ctr Intelligent Informat Retrieval, Dept Comp Sci, Amherst, MA 01003 USA
来源：
ADVANCES IN INFORMATION RETRIEVAL THEORY | 2009年 / 5766卷
关键词：
Cluster hypothesis; nearest neighbor test; relevant document networks; normalized mean reciprocal distance;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
We have found that the nearest neighbor (NN) test is an insufficient measure of the cluster hypothesis. The NN test is a local measure of the cluster hypothesis. Designers of new document-to-document similarity measures may incorrectly report effective clustering of relevant documents if they use the NN test alone. Utilizing a measure from net;work analysis, we present a new, global measure of the cluster hypothesis: normalized mean reciprocal distance. When used together with a, local measure, such as the NN test, this new global measure allows researchers to better measure the cluster hypothesis.
引用
收藏
页码：281 / +
页数：2
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