Crowdsourced Data Management: A Survey

Author(s):  
Guoliang Li ◽  
Jiannan Wang ◽  
Yudian Zheng ◽  
Michael Franklin
2018 ◽  
Author(s):  
Guoliang Li ◽  
Jiannan Wang ◽  
Yudian Zheng ◽  
Ju Fan ◽  
Michael J. Franklin

2016 ◽  
Vol 28 (9) ◽  
pp. 2296-2319 ◽  
Author(s):  
Guoliang Li ◽  
Jiannan Wang ◽  
Yudian Zheng ◽  
Michael J. Franklin

2015 ◽  
Vol 6 (1-2) ◽  
pp. 1-161 ◽  
Author(s):  
Adam Marcus ◽  
Aditya Parameswaran

Author(s):  
Guoliang Li ◽  
Yudian Zheng ◽  
Ju Fan ◽  
Jiannan Wang ◽  
Reynold Cheng

2017 ◽  
Author(s):  
Antoine Amarilli ◽  
Silviu Maniu ◽  
Pierre Senellart

We call data intensional when it is not directly available, but must be accessed through a costlyinterface. Intensional data naturally arises in a number of Web data management scenarios, suchas Web crawling or ontology-based data access. Such scenarios require us to model an uncertainview of the world, for which, given a query, we must answer the question “What is the best thingto do next?” Once data has been retrieved, the knowledge of the world is revised, and the wholeprocess is repeated, until enough knowledge about the world has been obtained for the particularapplication considered. In this article, we give an overview of the steps underlying all intensionaldata management scenarios, and illustrate them on three concrete applications: focused crawling,online influence maximization in social networks, and mining crowdsourced data.


2016 ◽  
Vol 62 ◽  
pp. 170-184 ◽  
Author(s):  
Atsuyuki Morishima ◽  
Shun Fukusumi ◽  
Hiroyuki Kitagawa

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