Automated Question Generation for Quality Control in Human Computation Tasks

被引：2

作者：

Seyler, Dominic ^{[1
]}

Yahya, Mohamed ^{[1
]}

Berberich, Klaus ^{[1
]}

Alonso, Omar ^{[2
]}

机构：

[1] Max Planck Inst Informat, Saarbrucken, Germany

[2] Microsoft Corp, Redmond, WA 98052 USA

来源：

PROCEEDINGS OF THE 2016 ACM WEB SCIENCE CONFERENCE (WEBSCI'16) | 2016年

关键词：

Honeypot Generation; Natural Language Questions;

D O I：

10.1145/2908131.2908210

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

When running large human computation tasks in the real-world, honeypots play an important role for assessing the overall quality of the work produced. The generation of such honeypots can be a significant burden on the task owner as they require specific characteristics in their design and implementation and continuous maintenance when operating data pipelines that include a human computation component. In this extended abstract we outline a novel approach for creating honeypots using automatically generated questions from a reference knowledge base with the ability to control such parameters as topic and difficulty.

引用

页码：360 / 362

页数：3

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