A visualization model based on adjacency data

被引：20

作者：

Condon, E

Golden, B ^{[1
]}

Lele, S

Raghavan, S

Wasil, E

机构：

[1] Univ Maryland, Rh Smith Sch Business, College Pk, MD 20742 USA

[2] Univ Maryland, Inst Res Elect & Appl Phys, College Pk, MD 20742 USA

[3] American Univ, Kogod Sch Business, Washington, DC 20016 USA

来源：

DECISION SUPPORT SYSTEMS | 2002年 / 33卷 / 04期

关键词：

visualization; Sammon map; multidimensional scaling;

D O I：

10.1016/S0167-9236(02)00003-9

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, we describe a model whose focus is on data visualization. We assume the data are provided in adjacency format, as is frequently the case in practice. As an example, individuals who buy item a are likely to buy or consider buying items b, c, and d, also. We present a simple technique for obtaining distance measures between data points. Armed with the resulting distance matrix, we show how Sammon maps can be used to visualize the data points. An application to the college selection process is discussed in detail. (C) 2002 Elsevier Science B.V. All rights reserved.

引用

页码：349 / 362

页数：14

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