Asking the Right Questions in Crowd Data Sourcing

被引：41

作者：

Boim, Rubi ^{[1
]}

Greenshpan, Ohad ^{[1
]}

Milo, Tova ^{[1
]}

Novgorodov, Slava ^{[1
]}

Polyzotis, Neoklis ^{[2
]}

Tan, Wang-Chiew ^{[2
,3
]}

机构：

[1] Tel Aviv Univ, Tel Aviv, Israel

[2] Univ Calif Santa Cruz, Santa Cruz, CA 95064 USA

[3] IBM Res, San Jose, CA USA

来源：

2012 IEEE 28TH INTERNATIONAL CONFERENCE ON DATA ENGINEERING (ICDE) | 2012年

关键词：

D O I：

10.1109/ICDE.2012.122

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Crowd-based data sourcing is a new and powerful data procurement paradigm that engages Web users to collectively contribute information. In this work we target the problem of gathering data from the crowd in an economical and principled fashion. We present AskIt!, a system that allows interactive data sourcing applications to effectively determine which questions should be directed to which users for reducing the uncertainty about the collected data. AskIt! uses a set of novel algorithms for minimizing the number of probing (questions) required from the different users. We demonstrate the challenge and our solution in the context of a multiple-choice question game played by the ICDE'12 attendees, targeted to gather information on the conference's publications, authors and colleagues.

引用

页码：1261 / 1264

页数：4