@inproceedings{3b05513bdc4c42d48210f187b438c0ab,
title = "CrowdOp: Query optimization for declarative crowdsourcing systems",
abstract = "We propose CROWDOP, a cost-based query optimization approach for declarative crowdsourcing systems. CROWDOP considers both cost and latency in the query optimization objectives and generates query plans that provide a good balance between the cost and latency. We develop efficient algorithms in CROWDOP for optimizing three types of queries: selection, join and complex selection-join queries. We validate our approach via extensive experiments by simulation as well as with the real crowd on Amazon Mechanical Turk.",
author = "Ju Fan and Meihui Zhang and Stanley Kok and Meiyu Lu and Ooi, \{Beng Chin\}",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 32nd IEEE International Conference on Data Engineering, ICDE 2016 ; Conference date: 16-05-2016 Through 20-05-2016",
year = "2016",
month = jun,
day = "22",
doi = "10.1109/ICDE.2016.7498417",
language = "English",
series = "2016 IEEE 32nd International Conference on Data Engineering, ICDE 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1546--1547",
booktitle = "2016 IEEE 32nd International Conference on Data Engineering, ICDE 2016",
address = "United States",
}