Name
Abstract | ||
|---|---|---|
As information systems are becoming sophisticated and mobile, cloud computing, social networking services are now very popular to people, the amount of data is rapidly increasing every year. Big data is data which should be analyzed by a company or an organization, but has not been tried to be analyzed or could not have been processed by current technology. In this paper, we introduce a big data model for recommender systems using social network data. The model incorporates factors related to social networks and can be applied to information recommendation with respect to various social behaviors that can increase the reliability of the recommended information. The big data model has the flexibility to be expanded to incorporate more sophisticated additional factors if needed. The experimental results using it in information recommendation and using map-reduce to process it show that it is a feasible model to be used for information recommendation. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/CGC.2012.125 | CGC |
Keywords | Field | DocType |
feasible model,information systems,big data,social networking service,various social behavior,information system,social network,social networks,recommender system,information recommendation,recommender systems,big data model,social network data,map-reduce,data model,recommended information,social networking (online),cloud computing,mobile computing | Recommender system,Mobile computing,Information system,Social behavior,World Wide Web,Social network,Computer science,Data model,Big data,Cloud computing | Conference |
ISBN | Citations | PageRank |
978-1-4673-3027-5 | 6 | 0.50 |
References | Authors | |
4 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaoyue Han | 1 | 6 | 0.84 |
| Lianhua Tian | 2 | 6 | 0.50 |
| Minjoo Yoon | 3 | 6 | 0.50 |
| Minsoo Lee | 4 | 315 | 31.33 |