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  • 标题:FAKE JOB FORECAST USING DATA MINING TECHNIQUES
  • 本地全文:下载
  • 作者:C.K. Gomathy ; Y.JEEVANKUMARREDDY ; T.suneel
  • 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
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