Name
Abstract | ||
|---|---|---|
The evolving of Internet technology allows people to communicate even they are far away from each other. More and more people share information and exchange their thoughts via the communities on the websites and become friends. A larger community usually attracts more users, therefore, how to enhance the development of a social network on the website is an important issue for the survival of a website. In this paper, we combine the social network features into the recommendation system. In addition to messages between nodes, the features of network structure are taken into consideration. Experimental results show that the recommendation accuracy of our method is higher than the existing method which is based on the message ratio. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/ASONAM.2011.68 | ASONAM |
Keywords | Field | DocType |
internet technology,message ratio,important issue,social network,network structure,recommender systems,existing method,web sites,internet,social network feature,recommendation system,social networking (online),recommendation accuracy,people share information,information sharing,network theory (graphs),web communities,recommender system,accuracy,decision trees,computer science,collaboration | Recommender system,Network mapping,Organizational network analysis,World Wide Web,Internet privacy,Social network,Computer science,Dynamic circuit network,The Internet,Intelligent computer network,Broadcast communication network | Conference |
ISBN | Citations | PageRank |
978-0-7695-4375-8 | 6 | 0.46 |
References | Authors | |
10 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bi-Ru Dai | 1 | 185 | 16.79 |
| Chang-yi Lee | 2 | 6 | 0.80 |
| Chih-Heng Chung | 3 | 10 | 2.55 |