Analyze and Recommend News Comments in E-Government

Author

Xie, Hongwei ; Yan, Xiangyu ; Sun, Jingyu ; Yu, Xueli

Author_Institution

Coll. of Comput. & Software, Taiyuan Univ. of Technol., Taiyuan, China

fYear

2010

fDate

7-9 May 2010

Firstpage

451

Lastpage

453

Abstract

With the development of Internet, more and more public users prefer to present their viewpoints of government policies. They often comment on some emergencies through news, blogs and so on. Their opinions influence decision makers of government to make right decisions. However, large numbers of news and related comments are produced when an emergency occurs and officers are very difficult to read and analyze all of them in seconds. Specially, comments usually are short texts and common clustering technologies are not suited to analyze them. In this paper, we firstly propose a framework based on semantic web technologies to recommend news and related comments in order to aid different officers to get their interesting news rapidly. Then, a new short text clustering method is discussed to analyze related comments. Finally, a news recommender system based on above approaches is introduced.

Keywords

Internet; decision making; government data processing; pattern clustering; recommender systems; text analysis; Internet; clustering technologies; decision makers; e-government; government policies; recommend news comments; recommender system; Electronic government; Ontologies; Recommender systems; Semantic Web; Semantics; Software; e-government; recommender system; semantic web; short text clustering;

fLanguage

English

Publisher

ieee

Conference_Titel

E-Business and E-Government (ICEE), 2010 International Conference on

Conference_Location

Guangzhou

Print_ISBN

978-0-7695-3997-3

Type

conf

DOI

10.1109/ICEE.2010.122

Filename

5590637