[Dbworld] CFP of JCST Special Issue on Crowdsourced Data Management

Call for Papers of JCST

Special Section: Crowdsourced Data Management

Journal of Computer Science and Technology (JCST)

Aims and Scope
Many important data management and analytics tasks cannot be completely addressed by automated processes. These tasks, such as entity resolution, sentiment analysis, and image recognition can be enhanced through the use of human cognitive ability. Crowdsourcing platforms are an effective way to harness the capabilities of people (i.e., the crowd) to apply human computation for such tasks. Thus, crowdsourced data management has become an area of increasing interest in research and industry. There still exist many challenges on crowdsourced data management, such as task decomposition and assignment, answer aggregation, and quality control. This special issue aims to address these challenges to enable crowdsourced data management more effective and efficient.



Topic includes (but are not limited to the following)
* Fundamental crowdsourcing theory 
* Task decomposition and assignment
* Answer aggregation
* Quality control
* Crowdsourcing operations
* Crowdsourcing optimization
* Crowdsourcing applications, such as data cleaning and data integration
* Crowdsourcing survey



Leading Editor
Xiaofang Zhou, The University of Queensland, Brisbane 


Guest Editor
Guoliang Li, Tsinghua University, Beijing


Schedule
Submission due:            March 1, 2017
First review completed:    May 1, 2017 
Revision due:              June 1, 2017
Final decision:            July 1, 2017
Final manuscript due:      July 10, 2017
Expected publication:      September 5, 2017

Submission Procedure
All submissions must be done electronically through JCST's e-submission system at https://mc03.manuscriptcentral.com/jcst, with a manuscript type: "Special Section on Crowdsourced Data Management".

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