.png){kind=icon}
返回
An Author Gender Detection Method Using Whale Optimization Algorithm and Artificial Neural Network
.png){kind=icon}
OA
AI
DOI：10.1109/ACCESS.2020.2973509.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Author gender detection (AGD) is a serious and crucial issue in Internet security applications, in particular in email, messenger, and social network communications. Detecting the gender of communication partner helps preventing massive fraud and abuses happening through social media such as email, blogs, forums. Text and writings of people on the Internet have valuable information that can be used to identify the gender of an author. Machine learning and meta-heuristic algorithms are valuable techniques to extract hidden patterns useful for detecting gender of a text. In this paper, an artificial neural network (ANN) is employed as a classifier to detect the gender of an email author and the whale optimization algorithm (WOA) is used to find optimal weights and biases for improving the accuracy of the ANN classification. Through this combination of ANN and WOA an accuracy of 98 & x0025;, precision of 97.16 & x0025;, and recall of 99.67 & x0025; were achieved, which indicates the superiority of the proposed method on Bayesian networks, regression, decision tree, support vector machine, and ANN examined.
Keyword:
Author gender detection
machine learning
artificial neural network
whale optimization algorithm
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.6
论文数:
9.8W
被引数:
29.4W
机构
引用论文
The Late Eocene House Range Flora, Sevier Desert, Utah: Paleoclimate and Paleoelevation.png)
PALAIOS
PALAIOSIF0
PREAI
分享收藏
查看更多内容