A Note on the Effect of Term Weighting on Selecting Intrinsic Dimensionality of Data

被引：0

作者：

Kumar, Ch. Aswani ^{[1
]}

Srinivas, S. ^{[2
]}

机构：

[1] VIT Univ, Sch Comp Sci, Intelligent Syst Div, Vellore 632014, Tamil Nadu, India

[2] VIT Univ, Sch Sci & Human, Div Appl Math, Vellore 632014, Tamil Nadu, India

来源：

CYBERNETICS AND INFORMATION TECHNOLOGIES | 2009年 / 9卷 / 01期

关键词：

Dimensionality selection; Latent semantic indexing; Ssingular value decomposition; Term weighting;

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：

The effect of term weighting on selecting intrinsic dimensionality of data is discussed. Experiments are conducted, using different term weighting and dimensionality selection methods, on four testing document collections (namely Medline, Cranfield, CACM and CISI). The results point that transforming the data matrix using a term weighting scheme plays a vital role in identifying the intrinsic dimensionality.

引用

页码：5 / 12

页数：8

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