@inproceedings{56fc75a7d1234b70bc559aca453db980,
title = "The Combination of Decision in Crowds When the Number of Reliable Annotator Is Scarce",
abstract = "Crowdsourcing appears as one of cheap and fast solutions of distributed labor networks. Since the workers have various expertise levels, several approaches to measure annotators reliability have been addressed. There is a condition when annotators who give random answer are abundance and few number of expert is available Therefore, we proposed an iterative algorithm in crowds problem when it is hard to find expert annotators by selecting expert annotator based on EM-Bayesian algorithm, Entropy Measure, and Condorcet Jury{\textquoteright}s Theorem. Experimental results using eight datasets show the best performance of our proposed algorithm compared to previous approaches.",
keywords = "Annotator reliability, Crowdsourcing, EM algorithm",
author = "Raharjo, {Agus Budi} and Mohamed Quafafou",
note = "Publisher Copyright: {\textcopyright} 2017, Springer International Publishing AG.; 16th International Symposium on Intelligent Data Analysis, IDA 2017 ; Conference date: 26-10-2017 Through 28-10-2017",
year = "2017",
doi = "10.1007/978-3-319-68765-0_22",
language = "English",
isbn = "9783319687643",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "260--271",
editor = "Niall Adams and Allan Tucker and David Weston",
booktitle = "Advances in Intelligent Data Analysis XVI - 16th International Symposium, IDA 2017, Proceedings",
address = "Germany",
}