• Rajani Bongane
• Nivedita Gangurde
• Sukesha Shinde
• Subham Tanpure
• Prof. Anjali Almale

In step with the researches finished until date millions of students graduate every yr. The problem of consumer recruitment with accept as true with is a big problem. Automatic consumer Recruitment machine is a product which can be exceptional ideal for any agency’s recruitment procedure. The device could be strong enough for you to automatically extract the resume content and keep it in a shape form inside the Database. Class algorithm (Naïve Bayes) will be run at the profiles to perceive profile classes or lessons. Also the company can specify his criteria and also decide the importance level. Because the internet grows, amount of electronic text increases swiftly. This brings the benefit of attaining the records sources in a reasonably-priced and quick way. Textual content mining is useful method as they deliver the shortest precis of the document. But they're not often protected in the texts. There are proposed methods for automated keyword extraction. This machine additionally introduces such a method, which identifies the keywords with their frequencies and positions in the schooling set. It uses Naïve Bayesian Classifier with supervised getting to know for filtering the large amount of information. An automatic consumer Recruitment system using text mining & classification approach can deal with this hassle.

User Recruitment, Trust Evolution, Classification Algorithm, Keyword Extraction, Naïve Bayesian Classifier, Supervised Learning, Text Mining, Resume, etc.

"Trust Evaluation Mechanism for User Recruitment in Network Crowd-Sensing", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 9, page no.7-10, September-2020, Available :http://www.jetir.org/papers/JETIR2009202.pdf

"Trust Evaluation Mechanism for User Recruitment in Network Crowd-Sensing", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 9, page no. pp7-10, September-2020, Available at : http://www.jetir.org/papers/JETIR2009202.pdf