Advanced International Journal for Research

E-ISSN: 3048-7641   •   Impact Factor: 9.11

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 7, Issue 5 (September-October 2026) Submit your research before last 3 days of October to publish your research paper in the issue of September-October.
Submit Research Paper Join as a Reviewer

Plagiarism is checked by the leading plagiarism checker TurnItIn

Call for Paper

Volume 7 Issue 5
September-October 2026

Submit your research paper

Indexing Partners
Academia Advanced Sciences Index Bielefeld Academic Search Engine CiteSeer DRJI Google Scholar Independent Search Engine & Directory Network ISI (International Scientific Indexing) Issuu Mendeley Research Networks
RefSeek ResearcherId - Thomson Reuters ResearchGate Scirus Scribd Semantic Scholar Wiki for Call for Papers WorldCat Zenodo

Retrieval-Augmented Generation For Human Resource Decision Support: A Critical Review And Research Gap Analysis

Author(s) Ms. Ashwini Bharat Phalke, Dr. Vinod Kumar Bhutnal
Country India
Abstract Human resource (HR) departments hold much of their most valuable knowledge in unstructured documents such as resumes, skill matrices, appraisal notes and project briefs. Locating the right employee for a given project from this material is slow, inconsistent and increasingly impractical as repositories grow. Large language models (llms) offer a natural-language interface to such data, but used alone they cannot see private organizational records and are prone to fabricating plausible but unsupported statements. Retrieval-Augmented Generation (RAG) addresses both problems by grounding a generative model in passages retrieved from a trusted corpus at query time. This paper reviews the literature that underpins an HR chatbot built on RAG and the Gemini model family. It covers the evolution of person–job fit research, the foundations of dense retrieval and RAG, document chunking and vector indexing, known failure modes of RAG pipelines, evaluation methodology, and the fairness and privacy obligations that apply to hiring-related systems. The review identifies a gap: published RAG work concentrates on open-domain and scientific question answering, while few studies examine retrieval over heterogeneous HR records for candidate recommendation. A set of design implications and open research questions is derived for medium and large organizations, and a staged system design for HR project-assignment decision support is proposed together with an evaluation plan
Keywords Retrieval-Augmented Generation, Large Language Models, Human Resource Analytics, Person–Job Fit, Vector Databases, Semantic Search, Gemini, Conversational Agents.
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 7, Issue 5, September-October 2026
Published On 2026-10-19
View / Download PDF File

Share this



E-ISSN 3048-7641
CrossRef

CrossRef DOI is assigned to each research paper published in our journal.

AIJFR DOI prefix is
10.63363/aijfr

Downloads
Research Paper Format Copyright Permission Form and Undertaking Form Cover Page Vol 7 Isu 6Cover Page Vol 7 Isu 4Cover Page Vol 7 Isu 3

All research papers published on this website are licensed under Creative Commons Attribution-ShareAlike 4.0 International License, and all rights belong to their respective authors/researchers.

CC-BY-SA Open Access

About AIJFR
Fees & Payment
Current Issue
Publication Archive 		Submit Research Paper
Track Submission Status
Publication Guidelines
Publication Ethics
Peer Review & Plagiarism 		Join as a Reviewer
Editors & Reviewers
Reviewer Referral Program
Get Reviewer Membership Certi. 		Website/Journal Policies
Usage Policy
Content Policies
Privacy Policy
Contact Us +91-9898-79-39-59 editor@aijfr.com