Filters








1,484 Hits in 5.0 sec

Enhancing Person-Job Fit for Talent Recruitment

Chuan Qin, Hengshu Zhu, Tong Xu, Chen Zhu, Liang Jiang, Enhong Chen, Hui Xiong
2018 The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval - SIGIR '18  
To this end, in this paper, we propose a novel end to end Ability aware Person Job Fit Neural Network model, which has a goal of reducing the dependence on manual labour and can provide better interpretation  ...  As a result, the recruiters have to seek the intelligent ways for Person Job Fit, which is the bridge for adapting the right job seekers to the right positions.  ...  To this end, in this paper, we propose an end-to-end Abilityaware Person-Job Fit Neural Network (APJFNN) model, which has a goal of reducing the dependence on human labeling data and can provide better  ... 
doi:10.1145/3209978.3210025 dblp:conf/sigir/QinZXZJCX18 fatcat:o2uh53ozx5fmpatzwb7jk4it3a

Interview Choice Reveals Your Preference on the Market

Rui Yan, Ran Le, Yang Song, Tao Zhang, Xiangliang Zhang, Dongyan Zhao
2019 Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining - KDD '19  
We then incorporate the preference into the matching framework as an end-to-end learnable neural network.  ...  To this end, in this paper, we propose a novel matching network with preference modeled.  ...  The last hidden states from the hierarchical RNN sequence are matched by the cosine similarity in pairs, which is a simple and effective matching model [17] . • Person-Job Fit Neural Network (PJFNN).  ... 
doi:10.1145/3292500.3330963 dblp:conf/kdd/YanLSZZ019 fatcat:xpnii72iwzh6bpjco3iamvoeza

Person-job fit estimation from candidate profile and related recruitment history with co-attention neural networks [article]

Ziyang Wang, Wei Wei, Chenwei Xu, Jun Xu, Xian-Ling Mao
2022 arXiv   pre-print
In this paper, we propose a novel neural network approach for person-job fit, which estimates person-job fit from candidate profile and related recruitment history with co-attention neural networks (named  ...  In this way, the historical successful recruitment records are introduced to enrich the features of resumes and job postings and strengthen the current matching process.  ...  To the best of our knowledge, we are the first to model the experience of recruiters by introducing graph neural networks into the person-job fit task.  ... 
arXiv:2206.09116v1 fatcat:gmbvvd4pn5amhgkst47nepayte

A Hybrid Model to Profile and Evaluate Soft Skills of Computing Graduates for Employment

Hemalatha Ramalingam, Raja Sher Afgun Usmani, Ibrahim Abakar Targio Hashem, Thulasyammal Ramiah Pillai
2021 International Journal of Advanced Computer Science and Applications  
Emerging tools such as Game Based Assessments have been valuable in talent screening and matching soft skills for job selection.  ...  However, these techniques/models are rather stand alone and are unable to provide an objective measure of the effectiveness of their approach leading to mismatch of skills.  ...  in Neural Network and upon that, behaves exactly as the Neural Network.  ... 
doi:10.14569/ijacsa.2021.0120761 fatcat:3fg5wpxtmjgurbln6yzrpzlvaa

Research on Job Burnout Evaluation and Turnover Tendency Prediction of Knowledge Workers Based on BP Neural Network

Jiang Mengmeng, Jakaria Dasan, Li Xiaoxiao, Muhammad Arif
2022 Security and Communication Networks  
Boosting method added the fusion layer of the correlation analysis of job burnout and turnover intention to the neural network model to predict the turnover intention of employees.  ...  The weight of the job burnout evaluation index was determined by fuzzy hierarchy, and BP neural network model was established.  ...  At present, the competition for talents is becoming more and more fierce, and the enterprises hope to recruit talents, train talents, use talents, and retain talents in various ways, so as to maximize  ... 
doi:10.1155/2022/6370886 fatcat:cua3diojgje6fdp5pgcooqyrmu

AI Recruiting Tools at ShipIt2Me.com

Janice C. Sipior, Department of Accountancy & Information Systems Villanova University, Danielle R. Lombardi, Renata Gabryelczyk, Department of Accountancy & Information Systems Villanova University, Faculty of Economic Sciences University of Warsaw
2021 Communications of the Association for Information Systems  
The case introduces students to ShipIt2Me.com ("ShipIt2Me"), a fictitious American e-commerce company that developed an AI human resources recruiting tool to help it hire cloud computing talent.  ...  The teaching case summarizes AI concepts and the opportunity for students to examine the advantages and disadvantages of using AI tools in human resources recruiting.  ...  Acknowledgment We sincerely thank Sheneya Wilson for her suggestions on an earlier version.  ... 
doi:10.17705/1cais.04839 fatcat:h43ildtmvbf3rndtwup3v2ajka

AI-Powered HCM: The Analytics and Augmentations [chapter]

Kovvali Bhanu Prakash, Appidi Adi Sesha Reddy, Ravi Kiran K. Yasaswi
2021 Beyond Human Resources - Research Paths Towards a New Understanding of Workforce Management Within Organizations [Working Title]  
The HCM Functions have been augmenting, 'app'ified (an application form) a nerve in a large, diagnosing and detecting problems, proposing the promising solutions.  ...  The 'Human Capital' has always been a top challenge and 'Human Talents' are ever scarce resources even today.  ...  AI is replacing and heavily enhancing low-skilled and repetitive jobs that do not require emotional capabilities.  ... 
doi:10.5772/intechopen.100475 fatcat:3eoafsnpczh2zascvlusvbbgge

A Human Resource Demand Forecasting Method Based on Improved BP Algorithm

Xingguang Lu, Gengxin Sun
2022 Computational Intelligence and Neuroscience  
In light of this, this paper employs an improved BP neural network to construct a human resource demand forecasting system, resulting in a new quantitative forecasting method for human resource demand  ...  The reality is that even if an enterprise designs a human resource allocation plan in accordance with the corporate strategy, it is impossible for the enterprise to operate in full accordance with the  ...  In terms of BP neural network research, ParasKumar applies BP neural networks and the LM algorithm to road noise prediction, using traffic flow as an input parameter to forecast the influence of cars on  ... 
doi:10.1155/2022/3534840 pmid:35392044 pmcid:PMC8983221 fatcat:mx3h737lqrcn5e34vto4wnfy6m

Design and interactive performance of human resource management system based on artificial intelligence

Yangda Gong, Min Zhao, Qin Wang, Zhihan Lv, Chi-Hua Chen
2022 PLoS ONE  
Besides, the salary forecast model in the HRM system (HRMS) is designed based on the Back Propagation Neural Network (BPNN), and network structure, parameter initialization, and activation function of  ...  The purpose is to strengthen Human Resources Management (HRM) through information management using Artificial Intelligence (AI) technology.  ...  The information in the resume library of an enterprise is analyzed to verify the effect Recruitment bias caused by factors such as gender and age may arise during employee recruitment.  ... 
doi:10.1371/journal.pone.0262398 pmid:35089946 pmcid:PMC8797210 fatcat:js2dnpvmlrgvnc5kfkex43z63i

A Hierarchical Reasoning Graph Neural Network for The Automatic Scoring of Answer Transcriptions in Video Job Interviews [article]

Kai Chen, Meng Niu, Qingcai Chen
2020 arXiv   pre-print
Specifically, we construct a sentence-level relational graph neural network to capture the dependency information of sentences in or between the question and the answer.  ...  In this work, we propose a Hierarchical Reasoning Graph Neural Network (HRGNN) for the automatic assessment of question-answer pairs.  ...  With the increasing amount of online recruitment data, more and more interview related studies have emerged such as person-job (or talent-job) fit (Shen et al. 2018; Qin et al. 2018; Luo et al. 2019b;  ... 
arXiv:2012.11960v1 fatcat:a4yuinygqzedtc5w3gekesvplq

Construction and Simulation of a Strategic HR Decision Model Based on Recurrent Neural Network

Xiaorong Li, Lijun Zhang, Dongchen Li, Dan Guo, Miaochao Chen
2022 Journal of Mathematics  
In this paper, RNN (Recurrent Neural Network) algorithm is used to conduct an in-depth analysis of HR strategic decision-making and an HR strategic decision model is constructed for simulation.  ...  On this basis, the applicability of the BP neural network in HR strategic decision-making is analysed and demonstrated, a BP neural network-based HR strategic decision-making model for power supply enterprises  ...  Acknowledgments is work was supported by the Provincial Talent Cultivation Project, "Study on the Relationship between the Economic Behavior of Minority Farmers and the Ecological Environment in the Construction  ... 
doi:10.1155/2022/5390176 fatcat:jfqiz24qknfzvcsbw4behqkqhu

Toward a traceable, explainable, and fairJD/Resume recommendation system [article]

Amine Barrak, Bram Adams, Amal Zouaq
2022 arXiv   pre-print
In the last few decades, companies are interested to adopt an online automated recruitment process in an international recruitment environment.  ...  In this proposal, our aim is to explore how modern language models (based on transformers) can be combined with knowledge bases and ontologies to enhance the JD/Resume matching process.  ...  They used a Person-Job Fit Neural Network to learn the joint representations of Person-Job fitness from historical job applications.  ... 
arXiv:2202.08960v1 fatcat:52mjmfklefhsfh7fhflmkgrime

An Integrated Conceptual Model of 360-Degree Performance Appraisal and Candidate Forecasting Using Adaptive Neuro-Fuzzy Inference System

Khomsun Lelavijit, Supaporn Kiattisin
2020 Journal of Mobile Multimedia  
This article proposes an approach to minimizing subjective judgement in the effective employee evaluation in the existence of the multi-factor competency-based measures in a hierarchical structure using  ...  The predicting behavioural competencies of employees to make investment in human development more effective.  ...  [32] Such results emphasize the benefits of the fusion of fuzzy and neural network technologies as it facilitates an accurate initialization of the network in terms of the parameters of the fuzzy reasoning  ... 
doi:10.13052/jmm1550-4646.1642 fatcat:3ts3kg6vt5gxhctufbbqzw3twu

Unattached fractions and aerosol attached of radon progeny in indoor air

Mohery, A
2012 International Journal of Physical Sciences  
International Journal of Physical Sciences (IJPS) is an open access journal that publishes high-quality solicited and unsolicited articles, in English, in all Physics and chemistry including artificial  ...  intelligence, neural processing, nuclear and particle physics, geophysics, physics in medicine and biology, plasma physics, semiconductor science and technology, wireless and optical communications, materials  ...  Conclusions In current study, suspended sediment concentration were estimated by an neural differential evolution (NDE) and two different neural network approach using different combination of hydrological  ... 
doi:10.5897/ijps11.1360 fatcat:brggzy3aufczzkurjw5rtkyj4e

A Deep Learning-Based Framework for Human Resource Recommendation

Li Ming, Kuruva Lakshmanna
2022 Wireless Communications and Mobile Computing  
Additionally, a deep neural network is implemented to enhance the accuracy of the proposed model.  ...  The training accuracy and validation accuracy of the proposed model by implementing a deep neural network are observed as 95.67% and 94.53%.  ...  Acknowledgments The authors are thankful to the higher authorities for the facilities provided.  ... 
doi:10.1155/2022/2377143 fatcat:ixtbel25yjgorfzmv273c3ytx4
« Previous Showing results 1 — 15 out of 1,484 results