Name
Abstract | ||
|---|---|---|
Hybrid human/computer database systems promise to greatly expand the usefulness of query processing by incorporating the crowd for data gathering and other tasks. Such systems raise many implementation questions. Perhaps the most fundamental question is that the closed world assumption underlying relational query semantics does not hold in such systems. As a consequence the meaning of even simple queries can be called into question. Furthermore, query progress monitoring becomes difficult due to non-uniformities in the arrival of crowdsourced data and peculiarities of how people work in crowdsourcing systems. To address these issues, we develop statistical tools that enable users and systems developers to reason about query completeness. These tools can also help drive query execution and crowdsourcing strategies. We evaluate our techniques using experiments on a popular crowdsourcing platform. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/ICDE.2013.6544865 | ICDE |
Keywords | DocType | Citations |
crowdsourcing strategy,drive query execution,popular crowdsourcing platform,relational query semantics,query completeness,simple query,Crowdsourced enumeration query,crowdsourcing system,query progress monitoring,query processing,systems developer | Conference | 8 |
PageRank | References | Authors |
0.49 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Michael J. Franklin | 1 | 17423 | 1681.10 |
| Beth Trushkowsky | 2 | 198 | 11.32 |
| Purnamrita Sarkar | 3 | 323 | 28.13 |
| Tim Kraska | 4 | 2226 | 133.57 |