Research ArticleOpen AccessGoogle Scholar indexed
Predict Edges in Fliker Social Network Using Data Mining Method
Young Researchers Club, Shiraz Branch, Islamic Azad University, Shiraz, Iran
Young Researchers Club, Sepidan Branch, Islamic Azad University, Sepidan, Iran
Sharif University of Technology, Tehran, Iran
- 1 Young Researchers Club, Shiraz Branch, Islamic Azad University, Shiraz, Iran
- 2 Young Researchers Club, Sepidan Branch, Islamic Azad University, Sepidan, Iran
- 3 Sharif University of Technology, Tehran, Iran
Intelligent Information Management·Volume 04 (2012)·Pages 60–65·Published 25 May 2012·DOI10.4236/iim.2012.43009
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Abstract
Using social networking services is becoming more popular day by day. The websites of the social networks like face-book currently are among the most popular internet services just after giant portals such as Yahoo, MSN and search engines like Google. One of the main problems in analyzing these networks is the prediction of relationships between people in the network. The purpose of this paper is to forecast the friendship of a person with a new person using existing data on Flickr website accurately. In this paper, we achieved about 90% percent correct prediction with regards to the results which are obtained by using data mining methods.
KeywordsSocial NetworkData MiningLink PredictionRegression
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