A Novel Text Data Mining Method based on Neural Network and Its Application

Author(s):  
Liu Lei
2020 ◽  
Vol 38 (4) ◽  
pp. 3717-3725
Author(s):  
Jingyong Zhou ◽  
Yuan Guo ◽  
Yu Sun ◽  
Kai Wu

2018 ◽  
Vol 22 (3) ◽  
pp. 225-242 ◽  
Author(s):  
K. Mathan ◽  
Priyan Malarvizhi Kumar ◽  
Parthasarathy Panchatcharam ◽  
Gunasekaran Manogaran ◽  
R. Varadharajan

2014 ◽  
Vol 1049-1050 ◽  
pp. 1637-1640
Author(s):  
Lei Liu ◽  
Shao Qiang Wang ◽  
Quan Bao Gao

Data mining aims to excavate new knowledge from existing information. When it comes to test mining, a better way is to take the context into account In this study we present text mining procedures based on a neural network framework in order to identify indicative factors in the form of keywords within the medical record narratives. These keywords and their weight/value suggest an innovative way for justifying a CT scan request. Our purpose is to extend the reach of diagnosis beyond traditional processing of clinical data towards an efficient utilization of the narratives in medical records.


2013 ◽  
Vol 380-384 ◽  
pp. 1860-1863
Author(s):  
Ping Zhang Gou ◽  
Yong Zhong Tang

This study proposed a novel relational database data mining method based on the artificial neural network. It analyzed the disadvantages of the existed data mining methods and then introduced the novel algorithm. This algorithm discovered the implicit knowledge by training the data samples in the database. This study introduced the artificial neural network method training model and algorithm, and tested the method by an example.


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