DocumentCode :
3658405
Title :
Using a Combination Method of MDS and SOM to Visually Analyze Postpartum Depression Domain
Author :
Xi Meng;Ruifang Shen;Jianqiang Li;Jijiang Yang
Author_Institution :
People´ Public Security Univ. of China, Beijing, China
Volume :
3
fYear :
2015
fDate :
7/1/2015 12:00:00 AM
Firstpage :
95
Lastpage :
95
Abstract :
This study focused on a combination method that included MDS and SOM to visually reveal research topics in postpartum depression research domain from the bibliographic point of view. 391 documents which were under postpartum depression domain were used to be analyzed in this study. Considering that MDS and SOM each dimension reduction method has its own disadvantages, we used the two visualization techniques. The nonmetric MDS method (Sammon´s mapping) combined with self-organizing map was employed to separate documents based on their topics, and a cluster analysis was conducted. The experiment result proved that Sammon´s mapping combined with self-organizing map techniques yielded the better visualization effect in revealing postpartum depression domain.
Keywords :
"Data visualization","Pediatrics","XML","Text mining","Visualization","Artificial neural networks","Web mining"
Publisher :
ieee
Conference_Titel :
Computer Software and Applications Conference (COMPSAC), 2015 IEEE 39th Annual
Electronic_ISBN :
0730-3157
Type :
conf
DOI :
10.1109/COMPSAC.2015.226
Filename :
7273332
Link To Document :
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