Name
Abstract | ||
|---|---|---|
Harnessing a crowd of users for the collection of mass data (data sourcing) has recently become a wide-spread practice. One effective technique is based on games as a tool that attracts the crowd to contribute useful facts. We focus here on the data management layer of such games, and observe that the development of this layer involves challenges such as dealing with probabilistic data, combined with recursive manipulation of this data. These challenges are difficult to address using current declarative data management framework works, and we thus propose here a novel such framework, and demonstrate its usefulness in expressing different aspects in the data management of Trivia-like games. We have implemented a system prototype with our novel data management framework at its core, and we highlight key issues in the system design, as well as our experimentations that indicate the usefulness and scalability of the approach. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1145/2187836.2187942 | WWW |
Keywords | Field | DocType |
framework work,data management layer,system prototype,mass data,probabilistic data,declarative platform,current declarative data management,trivia-like game,system design,novel data management framework,data management,games,databases,probabilistic,crowdsourcing | Data mining,World Wide Web,Computer science,Crowdsourcing,Systems design,Probabilistic logic,Data management,Recursion,Scalability | Conference |
Citations | PageRank | References |
9 | 0.61 | 24 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Daniel Deutch | 1 | 345 | 41.49 |
| Ohad Greenshpan | 2 | 195 | 13.43 |
| Boris Kostenko | 3 | 13 | 1.43 |
| Tova Milo | 4 | 4074 | 1052.72 |