Name
Abstract | ||
|---|---|---|
The rapid growth of weblog provides a rich resource for social community mining. In this paper, we put forward a novel research problem of recommendation under the circumstance of a blog system. Most of the previous works usually focus on recommendation for registered blogger, few present a comprehensive investigations on recommendation for potential bloggers who have not provided personalized information in blog system. With the rapid popularity of social networks in recent years, non-personalized recommendation has become one of big challenges in different scenarios. We present a algorithm on the inhomogeneous graph to calculate the important value of an object, and then combined with similarity value to do recommendation. The algorithms which we proposed learn multi parameters in the random walk model, which is also very important in searching problems. The experimental results show that our proposed approaches can achieve good performance. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/CSSE.2008.857 | CSSE (1) |
Keywords | Field | DocType |
big challenge,inhomogeneous graph,random walk model,non-personalized recommendation,social network,social networks,rapid popularity,important value,nonpersonalized recommendation,social community mining,knowledge recommendation,similarity value,rapid growth,web sites,blog system,random walk,weblog,algorithm base,graph theory,learning algorithm,personalized information,information services,social communication,accuracy,internet,training data | Information system,Social network,Social community,Computer science,Popularity,Artificial intelligence,The Internet,Graph theory,Graph,Algorithm,Database,Machine learning,A* search algorithm | Conference |
Volume | ISBN | Citations |
1 | 978-0-7695-3336-0 | 0 |
PageRank | References | Authors |
0.34 | 5 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yang Zhi-Zhuo | 1 | 0 | 0.34 |
| Han Xie | 2 | 0 | 1.69 |
| Yang Wei | 3 | 2 | 3.09 |