Name
Abstract | ||
|---|---|---|
In this work we present the details of a large scale user profiling framework that we developed here in IBM on top of Apache Hadoop. We address the problem of extracting and maintaining a very large number of user profiles from large scale data. We first describe an efficient user profiling framework with high user profiling quality guarantees. We then describe a scalable implementation of the proposed framework in Apache Hadoop and discuss its challenges. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1145/1779599.1779603 | Proceedings of the 2010 Workshop on Massive Data Analytics on the Cloud |
Keywords | DocType | Citations |
hadoop,large scale data,large scale user,extracting user profile,quality guarantee,proposed framework,user profile,high user,large number,efficient user,scalable implementation,large scale,apache hadoop | Conference | 21 |
PageRank | References | Authors |
1.47 | 12 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Michal Shmueli-Scheuer | 1 | 89 | 16.11 |
| Haggai Roitman | 2 | 314 | 32.07 |
| David Carmel | 3 | 2530 | 156.30 |
| Yosi Mass | 4 | 574 | 60.91 |
| David Konopnicki | 5 | 377 | 144.72 |