{"title":"基于机器学习的虚假招聘检测系统","authors":"Arryan Sinha, Dr. G. Suseela","doi":"10.54473/ijtret.2022.6103","DOIUrl":null,"url":null,"abstract":"In order to avoid fraudulent online job postings, we use an automated tool that uses natural language processing (NLP) and classification techniques based on machine learning are suggested on paper. Using the NLP library SpaCy in python we have performed various analyzes such as semantic, syntactic, tokenization of the task profile extracting features and using a machine learning algorithm called Random Forest we have predicted its accuracy to classify a job profile as Real or Fake.","PeriodicalId":127327,"journal":{"name":"International Journal Of Trendy Research In Engineering And Technology","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"MACHINE LEARNING-BASED FAKE JOB RECRUITMENT DETECTION SYSTEM\",\"authors\":\"Arryan Sinha, Dr. G. Suseela\",\"doi\":\"10.54473/ijtret.2022.6103\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to avoid fraudulent online job postings, we use an automated tool that uses natural language processing (NLP) and classification techniques based on machine learning are suggested on paper. Using the NLP library SpaCy in python we have performed various analyzes such as semantic, syntactic, tokenization of the task profile extracting features and using a machine learning algorithm called Random Forest we have predicted its accuracy to classify a job profile as Real or Fake.\",\"PeriodicalId\":127327,\"journal\":{\"name\":\"International Journal Of Trendy Research In Engineering And Technology\",\"volume\":\"26 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal Of Trendy Research In Engineering And Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.54473/ijtret.2022.6103\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal Of Trendy Research In Engineering And Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.54473/ijtret.2022.6103","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
MACHINE LEARNING-BASED FAKE JOB RECRUITMENT DETECTION SYSTEM
In order to avoid fraudulent online job postings, we use an automated tool that uses natural language processing (NLP) and classification techniques based on machine learning are suggested on paper. Using the NLP library SpaCy in python we have performed various analyzes such as semantic, syntactic, tokenization of the task profile extracting features and using a machine learning algorithm called Random Forest we have predicted its accuracy to classify a job profile as Real or Fake.
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