Expression of Concern: Wang, C., Zhang, Q., Liu, W., Liu, Y. & Miao, L. Facial feature discovery for ethnicity recognition. WIREs Data Mining Knowl. Discov. 9, e1278 (2019). https://doi.org/10.1002/widm.1278
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引用次数: 0
Abstract
This Expression of Concern is for the above article, published online on August 2, 2018 in Wiley Online Library (wileyonlinelibrary.com), and has been published by agreement between the journal Editor-in-Chief, Dr. Witold Pedrycz, and Wiley Periodicals LLC. The expression of concern has been agreed due to concerns raised regarding possible misrepresentation of the data set of facial images used in this article. Based on information provided by the authors, data collection for the above mentioned article took place in 2014. However, it has subsequently been noted that images from this same data set have purportedly been used in both a 2010 article (1) and a 2018 article (in which the data reported was purportedly collected in 2012) (2), which were co-authored by the corresponding author of the above mentioned article. The journal therefore has concerns about when data collection actually took place. Additionally, Figure 1 in the above mentioned article appears to be the same as Figure 1 of the 2018 article (2), though there is no citation, and permission was not obtained to reuse the figure. Unfortunately, the authors have been unable to provide any further information to the journal to help clarify when data collection took place. As a result, the journal has decided to issue an Expression of Concern to readers.
期刊介绍:
The goals of Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery (WIREs DMKD) are multifaceted. Firstly, the journal aims to provide a comprehensive overview of the current state of data mining and knowledge discovery by featuring ongoing reviews authored by leading researchers. Secondly, it seeks to highlight the interdisciplinary nature of the field by presenting articles from diverse perspectives, covering various application areas such as technology, business, healthcare, education, government, society, and culture. Thirdly, WIREs DMKD endeavors to keep pace with the rapid advancements in data mining and knowledge discovery through regular content updates. Lastly, the journal strives to promote active engagement in the field by presenting its accomplishments and challenges in an accessible manner to a broad audience. The content of WIREs DMKD is intended to benefit upper-level undergraduate and postgraduate students, teaching and research professors in academic programs, as well as scientists and research managers in industry.