A quantitative method is developed for measuring the quality of network visualizations in terms of log-likelihood metrics resulted from Expectation Maximization (EM) clustering intrinsic and extrinsic attributes of network nodes.
%0 Conference Paper
%1 chen_measuring_2005
%A Chen, Chaomei
%D 2005
%K EM clustering,network metrics of quality visualization,quality
%P 405-405
%T Measuring the quality of network visualization
%X A quantitative method is developed for measuring the quality of network visualizations in terms of log-likelihood metrics resulted from Expectation Maximization (EM) clustering intrinsic and extrinsic attributes of network nodes.
@inproceedings{chen_measuring_2005,
abstract = {A quantitative method is developed for measuring the quality of network visualizations in terms of log-likelihood metrics resulted from Expectation Maximization (EM) clustering intrinsic and extrinsic attributes of network nodes.},
added-at = {2007-12-03T17:48:07.000+0100},
author = {Chen, Chaomei},
biburl = {https://www.bibsonomy.org/bibtex/2d687131ca01f35941de0f38eb5635ea7/sercarfe},
interhash = {121e99a69e6b6f3a7a65740968d9506b},
intrahash = {d687131ca01f35941de0f38eb5635ea7},
keywords = {EM clustering,network metrics of quality visualization,quality},
pages = {405-405},
timestamp = {2007-12-03T17:48:23.000+0100},
title = {Measuring the quality of network visualization},
year = 2005
}