Morris, SA; Wu, Z; Yen, G "A SOM mapping technique for visualizing documents in a database" IJCNN'01: INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-4, PROCEEDINGS. 2001. p.1914-1919 IEEE, New York

[Eugene Garfield]

Authors' email addresses are:
 samorri at okstate.edu
 wzheng at okstate.edu
 gyen at okstate.edu

TITLE:          A SOM mapping technique for visualizing documents in a
                database (Article, English)
AUTHOR:         Morris, SA; Wu, Z; Yen, G
SOURCE:         IJCNN'01: INTERNATIONAL JOINT CONFERENCE ON NEURAL
                NETWORKS, VOLS 1-4, PROCEEDINGS. 2001. p.1914-1919 I E E
                E, NEW YORK

SEARCH TERM(S):  SCIENTOMETRICS  rwork


ABSTRACT:       A method is introduced for mapping documents, based on
document citations, on a two dimensional map for clustering and
visualization for the application of technology forecasting. The citation
data is used to build an adjacency matrix which describes the document
set as an undirected graph. The dimensionality of the adjacency matrix is
reduced using principal components analysis. The reduced dimension data
is used to train a small rectangular self organizing map (SOM). After
training, each document's input vector is premultiplied by the SOM weight
matrix to find a spatial response across the SOM and the centroid of this
response is used to map the document, The ordination method is
demonstrated on a synthetic data set with good results. Further
encouraging results using an actual 118 polymer document dataset are also
shown.

AUTHOR ADDRESS: SA Morris, Oklahoma State Univ, Sch Elect & Comp Engn,
                Stillwater, OK 74078 USA