Name
Abstract | ||
|---|---|---|
Truth discovery is an important component of data cleaning and information integration. However, in the absence of knowledge, some truth could not be found from databases themselves. A possible solution is to involve crowds to find all the truth with the knowledge of crowds. In this paper, we propose a truth discovery framework based on active learning model with crowdsourcing. First, we give the basic voting algorithm BVote. Then we present the simple crowding-based truth discovery framework STDA based on BVote. Experimental results show that the STDA framework for truth discovery has improved significantly in accuracy with minimal efforts of workers. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/978-3-319-08010-9_48 | WEB-AGE INFORMATION MANAGEMENT, WAIM 2014 |
Keywords | Field | DocType |
truth discovery, crowdsourcing, active learning | Crowds,Information integration,Voting algorithm,Active learning,Crowding,Computer science,Crowdsourcing,Artificial intelligence,Machine learning | Conference |
Volume | ISSN | Citations |
8485 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 2 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chen Ye | 1 | 8 | 4.16 |
| Hongzhi Wang | 2 | 421 | 73.72 |
| Hong Gao | 3 | 1086 | 120.07 |
| Jianzhong Li | 4 | 3196 | 304.46 |
| Hui Xie | 5 | 41 | 8.93 |