The text mining and classification analyses on the relationship of Macau special administrative region´s policy addresses from 2012 to 2013

Author

Shianghau Wu ; Shunho Chu

Author_Institution

Fac. of Manage. & Adm., Macau Univ. of Sci. & Technol., Macau, China

fYear

2013

fDate

28-30 June 2013

Firstpage

1

Lastpage

3

Abstract

The study aimed at analyzing the keywords of the Macau Special Administrative Region´s 2012 and 2013 annual policy addresses. The contribution of the study included the following two points. First, the study used the text mining method in order to explore the content of policy address. Second, the study applied the SVM (Support Vector Machine) and random forests classification analysis to explore the relationship of the keywords between the two years´ policy addresses.

Keywords

data mining; government data processing; pattern classification; support vector machines; text analysis; Macau Special Administrative Region; SVM; annual policy address; random forest classification analysis; support vector machine; text classification analysis; text mining analysis; Accuracy; Algorithm design and analysis; Data models; Education; Predictive models; Support vector machines; Text mining; SVM (Support Vector Machine); policy address; random forests; text mining;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering, Management Science and Innovation (ICEMSI), 2013 International Conference on

Conference_Location

Taipa

Type

conf

DOI

10.1109/ICEMSI.2013.6914005

Filename

6914005