INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15
IntelliHire is a cutting-edge HR technology that uses information from Language Models (LLMs) to simplify the hiring process. Through the automation of processes including resume screening, question development, and applicant assessment, this platform strives to enable wiser recruiting choices. Recruiters are able to safely access the platform thanks to the system's user authentication feature. Upon submitting applicant resumes and job descriptions, IntelliHire applies natural language processing algorithms to assess the text. It provides a quantitative score to assess a candidate's suitability by identifying important talents and matching them with job criteria. To further improve the efficacy and speed of the interview process, the platform also produces questions that are specific to each candidate's résumé and job description. In order to ensure that candidates are assessed thoroughly and relevantly, these questions are adjusted dynamically depending on past replies. To help recruiters find the best prospects, IntelliHire provides visualizations that allow them to compare the scores and distributions of applicants. Also, by assessing interview replies and producing total ratings, it allows for full review. To simplify recruiting procedures and make wiser hiring choices, IntelliHire combines strong AI capabilities with user-friendly interfaces, representing a holistic solution for contemporary HR teams.
"IntelliHire-Smarter HR Decisions using LLM Intelligence", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.9, Issue 3, page no.1006 - 1010, March-2024, Available :http://www.ijsdr.org/papers/IJSDR2403140.pdf
Downloads:
000337364
Publication Details:
Published Paper ID: IJSDR2403140
Registration ID:210595
Published In: Volume 9 Issue 3, March-2024
DOI (Digital Object Identifier):
Page No: 1006 - 1010
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631
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