Please use this identifier to cite or link to this item: https://doi.org/10.1109/TKDE.2015.2407353
Title: CrowdOp: Query Optimization for Declarative Crowdsourcing Systems
Authors: Fan, Ju 
Zhang, Meihui 
Kok, Stanley 
Lu, Meiyu 
Ooi, Beng Chin 
Keywords: Crowdsourcing
Query optimization
Issue Date: 1-Aug-2015
Publisher: IEEE COMPUTER SOC
Citation: Fan, Ju, Zhang, Meihui, Kok, Stanley, Lu, Meiyu, Ooi, Beng Chin (2015-08-01). CrowdOp: Query Optimization for Declarative Crowdsourcing Systems. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 27 (8) : 2078-2092. ScholarBank@NUS Repository. https://doi.org/10.1109/TKDE.2015.2407353
Abstract: © 2015 IEEE. We study the query optimization problem in declarative crowdsourcing systems. Declarative crowdsourcing is designed to hide the complexities and relieve the user of the burden of dealing with the crowd. The user is only required to submit an SQL-like query and the system takes the responsibility of compiling the query, generating the execution plan and evaluating in the crowdsourcing marketplace. A given query can have many alternative execution plans and the difference in crowdsourcing cost between the best and the worst plans may be several orders of magnitude. Therefore, as in relational database systems, query optimization is important to crowdsourcing systems that provide declarative query interfaces. In this paper, we propose CrowdOp, a cost-based query optimization approach for declarative crowdsourcing systems. CrowdOp considers both cost and latency in query optimization objectives and generates query plans that provide a good balance between the cost and latency. We develop efficient algorithms in the CrowdOp for optimizing three types of queries: selection queries, join queries, 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.
Source Title: IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
URI: https://scholarbank.nus.edu.sg/handle/10635/172222
ISSN: 10414347
15582191
DOI: 10.1109/TKDE.2015.2407353
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