文章基本信息

标题：FAKE JOB FORECAST USING DATA MINING TECHNIQUES
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作者：C.K. Gomathy ; Y.JEEVANKUMARREDDY ; T.suneel 等
期刊名称：International Journal of Early Childhood Special Education
电子版ISSN：1308-5581
出版年度：2022
卷号：14
期号：5
页码：710-717
DOI：10.9756/INTJECSE/V14I5.70
语种：English
出版社：International Journal of Early Childhood Special Education
摘要：Due to advancements in contemporary technology and social communication in recent years, posting new job openings has become a very prevalent issue in today's society. As a result, the issue of predicting bogus job postings will be a major worry for everyone. Fake job posing prediction, like many other classification problems, is fraught with difficulties. The suggested system is made up of two primary components: a real-time fake job identifying unit and a model updating unit. This system normally has several lightweight detectors with it. A few of those discussed in this literature are: 1) Pre-banned domain finders which are used to tag posts having banned URLs. 2) near-duplicate identifiers designed to tag relevant post which has the near match of the pre-defined tagged conflict post. 3) Reliable identifier designed to tag the posts that are uploaded by the confidential users 4) The rest of the posts are identified using a per defined multi classifier unit.
关键词：false job prediction;semi-supervised