AN INTERNSHIP CAMPAIGN CASE STUDY SHOWING RESULTS OF ENHANCED RECRUITMENT PROCESSES USING NLP

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Julkaisussa:The International Scientific Conference eLearning and Software for Education vol. 2 (2021), p. 222
Päätekijä: Suciu, George, PhD
Muut tekijät: Pasat, Adrian, Birdici, Andrei, Pop, Iulia
Julkaistu:
"Carol I" National Defence University
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100 1 |a Suciu, George, PhD  |u Beia Consult International SRL, Peroni St. no. 12, Bucharest, Romania george@beia.ro 
245 1 |a AN INTERNSHIP CAMPAIGN CASE STUDY SHOWING RESULTS OF ENHANCED RECRUITMENT PROCESSES USING NLP 
260 |b "Carol I" National Defence University  |c 2021 
513 |a Conference Proceedings 
520 3 |a The use of AI presents numerous benefits for numerous industry verticals. AI technology facilitates the analysis of unstructured data from heterogeneous sources. The added value from AI technologies relies on the insight gained over the data, helping in the automation of specific activities, or tasks, or enhancing the human factor in taking better decisions. According to recent market studies, business intelligence and analytics showed to be the essential area in which AI can deliver results. Natural Language Processing (NLP) is the AI subdomain which deals with human language and speech. NLP sits at the crossroads between a diverse number of disciplines, from linguistics to computer science and engineering, and of course, AI. Opinion mining (or sentiment analysis) is a natural language processing technique applied to determine whether data is positive, negative, or neutral. NLP can be the perfect solution to solve the inefficiencies in the traditional recruiting model for both recruiters and candidates when it comes to candidate screening and profiling. Our case study presents a recruiting platform (SoMeDi) for internship campaigns that applies Sentiment Analysis (SA) techniques to improve the hiring processes aiming to increase the efficiency of internship campaigns by ensuring a better match between the candidates' professional skills and the hiring company fields of activity. The SoMeDi performs text analytics (sentiment analysis) over the candidates' input data, once it is collected when they register for various internship applications. The paper presents the SoMeDi recruiting platform architecture and the SA microservice, together with the results achieved after validating the platform in a real-world scenario. 
610 4 |a LinkedIn Corp Amazon.com Inc 
653 |a Linguistics 
653 |a Internships 
653 |a Decision analysis 
653 |a Data mining 
653 |a Sentiment analysis 
653 |a Neural networks 
653 |a Social networks 
653 |a Customer relationship management 
653 |a Recruitment 
653 |a Natural language processing 
653 |a Unstructured data 
653 |a Algorithms 
653 |a Automation 
653 |a Information management 
653 |a Candidates 
653 |a Intelligence (information) 
653 |a Labor market 
653 |a Case studies 
653 |a Artificial intelligence 
653 |a Personnel Selection 
653 |a Teaching Methods 
653 |a Computers 
653 |a Job Skills 
653 |a Apprenticeships 
653 |a Mathematics 
653 |a Social Media 
653 |a Language Processing 
653 |a Networks 
653 |a Internship Programs 
653 |a Speech 
653 |a Feedback (Response) 
700 1 |a Pasat, Adrian  |u Beia Consult International SRL, Peroni St. no. 12, Bucharest, Romania adrian.pasat@beia.ro 
700 1 |a Birdici, Andrei  |u Beia Consult International SRL, Peroni St. no. 12, Bucharest, Romania andrei.birdici@beia.ro 
700 1 |a Pop, Iulia  |u Beia Consult International SRL, Peroni St. no. 12, Bucharest, Romania iulia.pop@beia.ro 
773 0 |t The International Scientific Conference eLearning and Software for Education  |g vol. 2 (2021), p. 222 
786 0 |d ProQuest  |t Education Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/2641600704/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch 
856 4 0 |3 Full Text  |u https://www.proquest.com/docview/2641600704/fulltext/embedded/L8HZQI7Z43R0LA5T?source=fedsrch 
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