@inproceedings{c9e23b465bad407da6e78571209f8aa3,
title = "Label Aggregation for Crowdsourcing with Bi-Layer Clustering",
abstract = "This paper proposes a novel general label aggregation method for both binary and multi-class labeling in crowdsourcing, namely Bi-Layer Clustering (BLC), which clusters two layers of features-The conceptual-level and the physical-level features-To infer true labels of instances. BLC first clusters the instances using the conceptual-level features extracted from their multiple noisy labels and then performs clustering again using the physical-level features. It can facilitate tracking the uncertainty changes of the instances, so that the integrated labels that are likely to be falsely inferred on the conceptual layer can be easily corrected using the estimated labels on the physical layer. Experimental results on two real-world crowdsourcing data sets show that BLC outperforms seven state-of-The-Art methods.",
keywords = "Clustering, Crowdsourcing, Inference, Label aggregation",
author = "Jing Zhang and Sheng, {Victor S.} and Tao Li",
note = "Funding Information: This work was partially supported by the National Natural Science Foundation of China under Grant 61603186 and Grant 91646116, the Natural Science Foundation of Jiangsu Province, China, under Grant BK20160843, the China Postdoctoral Science Foundation under Grant 2016M590457, the Postdoctoral Science Foundation of Jiangsu Province, China, under Grant 1601199C, and the Scientific and Technological Support Project of Jiangsu Province, China, under Grant BE2016776. Publisher Copyright: {\textcopyright} 2017 Copyright held by the owner/author(s).; null ; Conference date: 07-08-2017 Through 11-08-2017",
year = "2017",
month = aug,
day = "7",
doi = "10.1145/3077136.3080679",
language = "English",
series = "SIGIR 2017 - Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval",
publisher = "Association for Computing Machinery, Inc",
pages = "921--924",
booktitle = "SIGIR 2017 - Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval",
}