Ju Fan, Zhewei Wei, Dongxiang Zhang,et al published a paper at TKDE2016

Sep 20th,2016

Ju Fan, Zhewei Wei, Dongxiang Zhang, Jingru Yang and Xiaoyong Du published a paper named “Distribution-Aware Crowdsourced Entity Collection” at IEEE Transactions on Knowledge and Data Engineering on Sep 20th,2016.

In this paper, they study a new research problem, distribution-aware crowdsourced entity collection (CROWDDEC): Given an expected distribution w.r.t. an attribute (e.g., region or year), it aims to collect a set of entities via crowdsourcing and minimize the difference of the entity distribution from the expected distribution.They propose an adaptive worker selection approach to address this problem.They prove the hardness of the problem, and develop effective estimation techniques as well as efficient worker selection algorithms to support this approach.They deployed the proposed approach on Amazon Mechanical Turk and the experimental results on two real datasets show that the approach achieves superiority on both effectiveness and efficiency.

IEEE Transactions on Knowledge and Data Engineering (TKDE) is an archival journal published monthly designed to inform researchers, developers, managers, strategic planners, users, and others interested in state-of-the-art and state-of-the-practice activities in the knowledge and data engineering area. The scope includes the knowledge and data engineering aspects of computer science, artificial intelligence, electrical engineering, computer engineering, and other appropriate fields. This Transactions provides an international and interdisciplinary forum to communicate results of new developments in knowledge and data engineering and the feasibility studies of these ideas in hardware and software.