Name
Abstract | ||
|---|---|---|
The social Web is a set of social relations that link people through the World Wide Web. Typical social Web applications which include social media and social network services etc. have already become the mainstream of web application. User-oriented and content generated by users are pivotal characteristics of the social Web. In the circumstance of massive user generated unstructured data, data sharing and recommendation approaches take a more important role than information retrieval approaches for data diffusion. In this paper, we analyze the disadvantages of current data sharing and recommendation methods and propose an automatic group mining approach based on user preferences, which lead to sufficient data diffusion and improve the sociability between users. Intuitively, the essential idea of our approach is that users who have the same preferences towards a set of interested topics could be gathered together as a Common Preferences Group (CPG). To evaluate the efficiency of the CPG mining algorithm and the accuracy of data recommendation based on our approach, the experiments use dataset collected from the most popular image sharing site Flickr. The experimental results prove the superiority of our new approach for data sharing and recommendation in social Web. © 2012 Springer-Verlag. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1007/978-3-642-32597-7_28 | DEXA (2) |
Keywords | Field | DocType |
common preference group,recommender system,social web | World Wide Web,Social media,Social network,Social web,Computer science,Data sharing,Cross-origin resource sharing,Unstructured data,Social Semantic Web,Web application | Conference |
Volume | Issue | ISSN |
7447 LNCS | PART 2 | 16113349 |
Citations | PageRank | References |
2 | 0.41 | 16 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dawen Jia | 1 | 2 | 1.09 |
| Cheng Zeng | 2 | 57 | 10.34 |
| Wenhui Nie | 3 | 2 | 1.76 |
| Zhihao Li | 4 | 136 | 17.95 |
| Zhiyong Peng | 5 | 395 | 83.65 |