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Published Paper Details:
Linguistic and Intelligent Machine for Automated Talent Aquisition - LIMAT
Authors
Nagarasan M,Kumaragurubaran K,Abinaya Sri K,Sughanthan M,Ramya R
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Keywords
LIMAT , AI Recruiter, AI Interview, E-Recruitment
Abstract
Abstract: The recruitment process in many organizations often struggles with inefficiencies, bias, and subjectivity due to traditional practices like manual resume screening, unstructured interviews, and generic assessments. To address these challenges, our project introduces LIMAT - Linguistic & Intelligent Machine for Automated Talent Acquisition, an AI-powered system designed to automate and streamline the hiring process LIMAT leverages Machine Learning (ML) and Natural Language Processing (NLP) to intelligently analyze candidate profiles, dynamically generate role-specific questions, and evaluate both textual and verbal responses. It automates resume screening by extracting relevant skills, experience, and qualifications, ensuring quick and accurate candidate-job matching. By minimizing human biases through data driven evaluations, LIMAT promotes fair and objective hiring practices. It supports asynchronous interviews and analyzes both written and spoken responses using sentiment analysis and confidence scoring, helping recruiters make better decisions. LIMAT also ranks candidates based on their overall performance and can provide instant, constructive feedback to improve the candidate experience. Furthermore, it integrates easily with existing HR systems and Applicant Tracking Systems (ATS), making it a scalable and cost effective solution for organizations of all sizes. By significantly reducing the time-to-hire and recruiter workload, LIMAT transforms talent acquisition into a more efficient, fair, and intelligent process. LIMAT not only enhances the efficiency of recruitment but also brings innovation to every stage of the hiring pipeline. Its ability to dynamically generate interview questions tailored to specific job roles ensures that each candidate is evaluated on relevant criteria, improving the accuracy of talent assessment. The system's advanced verbal and textual analysis helps identify communication skills, domain knowledge, and emotional intelligence, offering a holistic view of each applicant. With built-in scalability, LIMAT can seamlessly handle large volumes of applications without compromising evaluation quality, making it ideal for organizations with high recruitment demands. Additionally, its integration capabilities with existing HR tools allow for smooth adoption without disrupting current workflows. By automating repetitive tasks and offering consistent, unbiased assessments, LIMAT empowers recruiters to focus on strategic decision making and helps organizations attract and retain top talent in a competitive job market.
IJCRT's Publication Details
Unique Identification Number - IJCRT25A5524
Paper ID - 287592
Author type - Indian Author
Page Number(s) - n267-n275
Pubished in - Volume 13 | Issue 5 | May 2025
DOI (Digital Object Identifier) -
No Of Downloads - 87
Author Country - India, 641107, Coimbatore, Coimbatore, 641107, Science and Technology
Publisher Name - IJPUBLICATION | www.ijcrt.org | ISSN : 2320-2882
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Nagarasan M,Kumaragurubaran K,Abinaya Sri K,Sughanthan M,Ramya R, "Linguistic and Intelligent Machine for Automated Talent Aquisition - LIMAT", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.13, Issue 5, pp.n267-n275, May 2025, Available at :http://www.ijcrt.org/papers/IJCRT25A5524.pdf
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The International Journal of Creative Research Thoughts (IJCRT) aims to explore advances in research pertaining to applied, theoretical and experimental Technological studies.
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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