A method for ranking news sources, topics and articles

Author

Mao, Xi ; Chen, Wei

Author_Institution

Zhejiang Lab. of Service Robot, Zhejiang Univ., Hangzhou, China

Volume

4

fYear

2010

fDate

16-18 April 2010

Abstract

With numerous news available on the Web every day, the needs for effective news ranking algorithms to satisfy users´ requirements are continuously increasing. Though it has attracted lots of interests in the commercial world, little academic research has been done about news ranking. In this paper, we introduce a virtual graph model to describe the properties of news. Based on the model, we propose a ranking algorithm which can fully exploit the reinforcement between news sources, topics and articles. Our ranking algorithm can be processed on line. In the experiments, it shows good results with huge data from EagleRadio, an academic news recommending system.

Keywords

Internet; search engines; EagleRadio; academic news recommending system; academic research; ranking news articles; ranking news sources; ranking news topics; virtual graph model; Aggregates; Computer science; Data mining; Displays; Educational institutions; Joining processes; Laboratories; Search engines; Service robots; Web pages; Information Extraction; News Engine; News Ranking; News Topic;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Engineering and Technology (ICCET), 2010 2nd International Conference on

Conference_Location

Chengdu

Print_ISBN

978-1-4244-6347-3

Type

conf

DOI

10.1109/ICCET.2010.5485653

Filename

5485653