TY - JOUR
T1 - CDB
T2 - 44th International Conference on Very Large Data Bases, VLDB 2018
AU - Li, Guoliang
AU - Chai, Chengliang
AU - Fan, Ju
AU - Weng, Xueping
AU - Li, Jian
AU - Zheng, Yudian
AU - Li, Yuanbing
AU - Yu, Xiang
AU - Zhang, Xiaohang
AU - Yuan, Haitao
N1 - Publisher Copyright:
© 2018 VLDB Endowment.
PY - 2018
Y1 - 2018
N2 - Crowd-powered database systems can leverage the crowd's ability to address machine-hard problems, e.g., data integration. Existing crowdsourcing systems adopt the traditional tree model to select a good query plan. However, the tree model can optimize the I/O cost but cannot optimize the monetary cost, latency and quality, which are three important optimization goals in crowdsourcing. To address this limitation, we demonstrate CDB, a crowd-powered database system. CDB proposes a new graph-based model that adopts a fine-grained tuple-level optimization model which significantly outperforms existing coarse-grained tree-based optimization models. Moreover, CDB provides a unified frame- work to simultaneously optimize the monetary cost, quality and latency. We have deployed CDB on well-known crowd- sourcing platforms and users can easily use our system to deploy their applications. We will demonstrate how to use CDB to address real-world applications, including web table integration and entity collection.
AB - Crowd-powered database systems can leverage the crowd's ability to address machine-hard problems, e.g., data integration. Existing crowdsourcing systems adopt the traditional tree model to select a good query plan. However, the tree model can optimize the I/O cost but cannot optimize the monetary cost, latency and quality, which are three important optimization goals in crowdsourcing. To address this limitation, we demonstrate CDB, a crowd-powered database system. CDB proposes a new graph-based model that adopts a fine-grained tuple-level optimization model which significantly outperforms existing coarse-grained tree-based optimization models. Moreover, CDB provides a unified frame- work to simultaneously optimize the monetary cost, quality and latency. We have deployed CDB on well-known crowd- sourcing platforms and users can easily use our system to deploy their applications. We will demonstrate how to use CDB to address real-world applications, including web table integration and entity collection.
UR - http://www.scopus.com/inward/record.url?scp=85058888170&partnerID=8YFLogxK
U2 - 10.14778/3229863.3236226
DO - 10.14778/3229863.3236226
M3 - Conference article
AN - SCOPUS:85058888170
SN - 2150-8097
VL - 11
SP - 1926
EP - 1929
JO - Proceedings of the VLDB Endowment
JF - Proceedings of the VLDB Endowment
IS - 12
Y2 - 27 August 2018 through 31 August 2018
ER -