JobMatchAI An Intelligent Job Matching Platform Using Knowledge Graphs, Semantic Search and Explainable AI
Mayank Vyas, Abhijit Chakraborty, Vivek Gupta

TL;DR
JobMatchAI is an advanced job matching platform that combines knowledge graphs, semantic search, and explainable AI to improve candidate matching accuracy and transparency in recruitment processes.
Contribution
It introduces a production-ready system integrating Transformer embeddings, skill knowledge graphs, and interpretable reranking, along with a new benchmark and hybrid retrieval stack.
Findings
Enhanced candidate retrieval accuracy across multiple tasks.
Provides transparent, factor-wise explanations for match scores.
Demonstrates effectiveness through benchmark and real-world deployment.
Abstract
Recruiters and job seekers rely on search systems to navigate labor markets, making candidate matching engines critical for hiring outcomes. Most systems act as keyword filters, failing to handle skill synonyms and nonlinear careers, resulting in missed candidates and opaque match scores. We introduce JobMatchAI, a production-ready system integrating Transformer embeddings, skill knowledge graphs, and interpretable reranking. Our system optimizes utility across skill fit, experience, location, salary, and company preferences, providing factor-wise explanations through resume-driven search workflows. We release JobSearch-XS benchmark and a hybrid retrieval stack combining BM25, knowledge graph and semantic components to evaluate skill generalization. We assess system performance on JobSearch-XS across retrieval tasks, provide a demo video, a hosted website and installable package.
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Taxonomy
TopicsAdvanced Graph Neural Networks · Multimodal Machine Learning Applications · Topic Modeling
