论文标题
使用关联规则挖掘方法对针对妇女的骚扰的影响分析：孟加拉国的潜在
Impact Analysis of Harassment Against Women Using Association Rule Mining Approaches: Bangladesh Prospective
论文作者
论文摘要
近年来，人们注意到妇女在社会的每个部门都取得了进步。他们参与每个领域，例如教育，就业市场，社会工作等，都以显着的速度增加。在过去的几年中，政府一直在为每个部门的妇女提高妇女的发展，通过进行几项研究工作和活动，并为几个组织提供激励妇女的资金。尽管妇女在几个领域的参与正在增加，但最大的担忧是她们的进步面临着几个障碍，而性骚扰是其中之一也就不足为奇了。在孟加拉国，针对妇女，尤其是学生的骚扰是一个普遍的现象，这正在增加。在本文中，一种基于调查的和APRIORI算法用于分析几个年龄组骚扰的几种影响。此外，通过Apriori算法和F.P.的关联规则挖掘分析了一些因素，例如骚扰频繁影响，大多数脆弱的群体，主要面临骚扰的妇女，骚扰等人的涉嫌骚扰等。生长算法。然后，简要显示了两种算法之间的性能的比较。为此，已经从各个年龄段仔细收集了数据。
In recent years, it has been noticed that women are making progress in every sector of society. Their involvement in every field, such as education, job market, social work, etc., is increasing at a remarkable rate. For the last several years, the government has been trying its level best for the advancement of women in every sector by doing several research work and activities and funding several organizations to motivate women. Although women's involvement in several fields is increasing, the big concern is they are facing several barriers in their advancement, and it is not surprising that sexual harassment is one of them. In Bangladesh, harassment against women, especially students, is a common phenomenon, and it is increasing. In this paper, a survey-based and Apriori algorithm are used to analyze the several impacts of harassment among several age groups. Also, several factors such as frequent impacts of harassment, most vulnerable groups, women mostly facing harassment, the alleged person behind harassment, etc., are analyzed through association rule mining of Apriori algorithm and F.P. Growth algorithm. And then, a comparison of performance between both algorithms has been shown briefly. For this analysis, data have been carefully collected from all ages.
