# Modeling Two-Way Selection Preference for Person-Job Fit

arXiv: https://arxiv.org/abs/2208.08612 · HTML: https://mlsanity.com/paper/2208.08612/

## Key facts

- Cited by 18 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Aug 2022.

## Built on by (most cited first, 18 of 18)

- [Exploring Large Language Model for Graph Data Understanding in Online Job Recommendations](https://mlsanity.com/paper/2307.05722/) (2023)
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- [Large Language Model with Graph Convolution for Recommendation](https://mlsanity.com/paper/2402.08859/) (2024)
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- [Revisiting Reciprocal Recommender Systems: Metrics, Formulation, and Method](https://mlsanity.com/paper/2408.09748/) (2024)
- [ConFit v2: Improving Resume-Job Matching using Hypothetical Resume Embedding and Runner-Up Hard-Negative Mining](https://mlsanity.com/paper/2502.12361/) (2025)
- [A Conversation is Worth A Thousand Recommendations: A Survey of Holistic Conversational Recommender Systems](https://mlsanity.com/paper/2309.07682/) (2023)
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- [DISCO: A Hierarchical Disentangled Cognitive Diagnosis Framework for Interpretable Job Recommendation](https://mlsanity.com/paper/2410.07671/) (2024)
- [ConFit: Improving Resume-Job Matching using Data Augmentation and Contrastive Learning](https://mlsanity.com/paper/2401.16349/) (2024)
- [Challenges and Opportunities of NLP for HR Applications: A Discussion Paper](https://mlsanity.com/paper/2405.07766/) (2024)
- [An Efficient Long-Context Ranking Architecture With Calibrated LLM Distillation: Application to Person-Job Fit](https://mlsanity.com/paper/2601.10321/) (2026)
- [An IPW-based Unbiased Ranking Metric in Two-sided Markets](https://mlsanity.com/paper/2307.10204/) (2023)
- [Professional Network Matters: Connections Empower Person-Job Fit](https://mlsanity.com/paper/2401.00010/) (2023)
- [CUPID: A Real-Time Session-Based Reciprocal Recommendation System for a One-on-One Social Discovery Platform](https://mlsanity.com/paper/2410.18087/) (2024)
- [MHSNet:An MoE-based Hierarchical Semantic Representation Network for Accurate Duplicate Resume Detection with Large Language Model](https://mlsanity.com/paper/2508.13676/) (2025)
- [Beyond Match Maximization and Fairness: Retention-Optimized Two-Sided Matching](https://mlsanity.com/paper/2602.15752/) (2026)

## Abstract (arXiv)

Person-job fit is the core technique of online recruitment platforms, which can improve the efficiency of recruitment by accurately matching the job positions with the job seekers. Existing works mainly focus on modeling the unidirectional process or overall matching. However, recruitment is a two-way selection process, which means that both candidate and employer involved in the interaction should meet the expectation of each other, instead of unilateral satisfaction. In this paper, we propose a dual-perspective graph representation learning approach to model directed interactions between candidates and jobs. To model the two-way selection preference from the dual-perspective of job seekers and employers, we incorporate two different nodes for each candidate (or job) and characterize both successful matching and failed matching via a unified dual-perspective interaction graph. To learn dual-perspective node representations effectively, we design an effective optimization algorithm, which involves a quadruple-based loss and a dual-perspective contrastive learning loss. Extensive experiments on three large real-world recruitment datasets have shown the effectiveness of our approach.