The resourcefulness of crowdsourcing can be used to handle a wide range of complex
macro-tasks, such as travel planning, translation, and software development. Multi-phase …

With the continuous popularization of smart devices, Spatial Crowdsourcing (SC) came into
being a novel paradigm of collecting smart sensing. As a core issue, the task assignment …

When a crowdsourcing approach is used to assist the classification of a set of items, the
main objective is to classify this set of items by aggregating the worker-provided labels. A …

Many data-intensive applications that use machine learning or artificial intelligence
techniques depend on humans providing the initial dataset, enabling algorithms to process …

With the rapid development of crowdsourcing platforms that aggregate the intelligence of
Internet workers, crowdsourcing has been widely utilized to address problems that require …

Crowdsourcing is a relatively inexpensive and efficient mechanism to collect annotations of
data from the open Internet. Crowdsourcing workers are paid for the provided annotations …

There are many factors that affect the quality of data received from crowdsourcing, including
cognitive biases, varying levels of expertise, and varying subjective scales. This work …

近年来, 众包为传统数据管理提供了一种通过汇聚群体智慧求解问题的新模式,
并成为当前数据库领域的研究热点之一. 特别是随着移动互联网技术与共享经济模式的快速发展 …

众包测试是一种新兴的软件测试方式, 得到了学术界和工业界的广泛关注.
系统地总结了近年来众包软件测试研究的学术文献以及工业界实践进展: 首先 …

Crowdsourcing has been used in computational pathology to generate cell and cell nuclei
annotations for machine learning. Herein, we broaden its scope to the previously unsolved …