Paper Info
Title
A Ranking Model Based on Credit for Social News Website.
Abstract
Social news websites were popular for a time, but recently the traffics of some social news websites have been slowing down, even some of them went out of business. It's caused partly by the emergence of massive spam news and the news publication algorithm heavily relying on the ranking of senior users while ignoring the ranking of ordinary users. In order to solve these problems, this paper proposes a ranking model based on credit. On the technology, utilizes the qualitative mapping as the credit threshold activation model, uses the K-means method for classifying the users and attribute ranging model to calculate the value of the user credit. The simulation experiment shows this model can effectively reduce the spam news and pay more attention on regular users.
Year
DOI
Venue
2011
10.1007/978-3-642-24273-1_52
Communications in Computer and Information Science
Keywords
DocType
Volume
Attribute Theory,K-means,Ranking Model
Conference
238
Issue
ISSN
Citations 
null
1865-0929
2
PageRank 
References 
Authors
0.78
2
3
Name
Order
Citations
PageRank
Guanglin Xu1269.95
Xiaolin Xu226825.21
Jiali Feng33111.84