从人群中获得一切
Getting It All from the Crowd
摘要：
混合人/计算机系统通过将人群合并用于数据收集和其他任务，有望极大地扩展查询处理的有用性。这样的系统提出了许多数据库系统实现的问题。也许最根本的是，关系查询语义背后的封闭世界假设在这样的系统中不成立。因此，即使是简单的查询的含义也会受到质疑。此外，由于众包数据到达的不均匀性和人们如何在众包系统中工作的特殊性，查询进度监控变得困难。为了解决这些问题，我们开发了统计工具，使用户和系统开发人员的原因之间的权衡时间/成本和完整性。这些工具还可以帮助推动查询执行和众包策略。我们评估我们的技术，使用一个流行的众包平台上的实验。
英文摘要：
Hybrid human/computer systems promise to greatly expand the usefulness of query processing by incorporating the crowd for data gathering and other tasks. Such systems raise many database system implementation questions. Perhaps most fundamental 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 tradeoffs between time/cost and completeness. These tools can also help drive query execution and crowdsourcing strategies. We evaluate our techniques using experiments on a popular crowdsourcing platform.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
