Academic literature on the topic 'Job matching system'

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Journal articles on the topic "Job matching system"

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Sagar, Dr Y. "Intelligent Resume Matching System." International Journal for Research in Applied Science and Engineering Technology 13, no. 5 (2025): 7365–73. https://doi.org/10.22214/ijraset.2025.70220.

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Optimally efficient and smart resume screening is a key factor towards optimizing the recruitment processes, particularly with the recent huge number of applicant resumes in modern day labor markets. The contribution put forward herein suggests an Intelligent Resume Matching System to efficiently automate shortlisting resumes against vacancy announcements based on powerful natural language processing (NLP) methodologies and machine learning approaches The system makes use of BERT-based sentence transformers to create high-dimensional contextual embeddings from job postings and resumes both, di
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Chala, Sisay Adugna, Fazel Ansari, Madjid Fathi, and Kea Tijdens. "Semantic matching of job seeker to vacancy: a bidirectional approach." International Journal of Manpower 39, no. 8 (2018): 1047–63. http://dx.doi.org/10.1108/ijm-10-2018-0331.

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Purpose The purpose of this paper is to propose a framework of an automatic bidirectional matching system that measures the degree of semantic similarity of job-seeker qualifications and skills, against the vacancy provided by employers or job-agents. Design/methodology/approach The paper presents a framework of bidirectional jobseeker-to-vacancy matching system. Using occupational data from various sources such as the WageIndicator web survey, International Standard Classification of Occupations, European Skills, Competences, Qualifications, and Occupations as well as vacancy data from variou
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Ni, Qing. "Deep Neural Network Model Construction for Digital Human Resource Management with Human-Job Matching." Computational Intelligence and Neuroscience 2022 (May 19, 2022): 1–12. http://dx.doi.org/10.1155/2022/1418020.

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This article uses deep neural network technology and combines digital HRM knowledge to research human-job matching systematically. Through intelligent digital means such as 5G communication, cloud computing, big data, neural network, and user portrait, this article proposes the design of the corresponding digital transformation strategy of HRM. This article further puts forward the guaranteed measures in enhancing HRM thinking and establishing HRM culture to ensure the smooth implementation of the digital transformation strategy of the HRM. This system uses charts for data visualization and fl
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Parkar, Ameya, Mona Deshmukh, and Girish Deshmukh. "Job Recommendation System." International Journal of Basic and Applied Sciences 14, no. 3 (2025): 163–69. https://doi.org/10.14419/mhjxnq18.

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Online recruitment platforms have led to a surge in job applications, creating challenges for companies in managing and reviewing them ‎efficiently. With the exponential growth of online job postings and user profiles, the challenge of matching the right job to the right candidate has become increasingly complex. Job recommendation systems aim to streamline this process by leveraging advanced algorithms to ‎suggest relevant job opportunities to job seekers based on their skills, experience, and preferences. Our proposed technique performs better ‎in terms of personalized job recommendations to
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Guo, Shiqiang, Folami Alamudun, and Tracy Hammond. "RésuMatcher: A personalized résumé-job matching system." Expert Systems with Applications 60 (October 2016): 169–82. http://dx.doi.org/10.1016/j.eswa.2016.04.013.

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Shakya, Aman, and Subhash Paudel. "Job-Candidate Matching using ESCO Ontology." Journal of the Institute of Engineering 15, no. 1 (2019): 1–13. http://dx.doi.org/10.3126/jie.v15i1.27699.

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Skills management is one of the key factors to address the increasing competitiveness among different companies. Suitable knowledge representation and approach for matching skills and competences in job vacancies and candidate profiles can support human resources management automation through suitable matching and ranking services. This paper presents an approach for matchmaking between skills demand and supply through skill profiles enrichment and matching supply and demand profiles over multiple criteria. This work builds upon methods for profile modeling, information enrichment and multi-cr
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A .Tejaswini, Mrs. "AUTOMATED RESUME SCREENING USING NLP AND MACHINE LEARNING." International Scientific Journal of Engineering and Management 04, no. 05 (2025): 1–7. https://doi.org/10.55041/isjem03751.

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ABSTRACT: This project presents a machine learning-based resume screening system that extracts IT hard skills, soft skills, education, and experience from resumes and job descriptions. Using algorithms like Support Vector Classifier (SVC) and Random Forest, the system ensures accurate skill extraction and semantic matching. It provides personalized recommendations by highlighting key skills and relevant experience, helping job seekers make informed career decisions.The system supports multiple resume formats and adapts to changing market trends. A bidirectional semantic matching approach is us
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Alsaif, Suleiman Ali, Minyar Sassi Hidri, Hassan Ahmed Eleraky, Imen Ferjani, and Rimah Amami. "Learning-Based Matched Representation System for Job Recommendation." Computers 11, no. 11 (2022): 161. http://dx.doi.org/10.3390/computers11110161.

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Job recommender systems (JRS) are a subclass of information filtering systems that aims to help job seekers identify what might match their skills and experiences and prevent them from being lost in the vast amount of information available on job boards that aggregates postings from many sources such as LinkedIn or Indeed. A variety of strategies used as part of JRS have been implemented, most of them failed to recommend job vacancies that fit properly to the job seekers profiles when dealing with more than one job offer. They consider skills as passive entities associated with the job descrip
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Liala Almalki. "BERT-based Job Recommendation System Using LinkedIn Dataset." Journal of Information Systems Engineering and Management 10, no. 8s (2025): 280–91. https://doi.org/10.52783/jisem.v10i8s.1026.

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Amidst rapid technological progress, bridging the gap between job seekers and employers has become increasingly important as the job market evolves. This research presents a job recommendation system that leverages the Bidirectional Encoder Representations from Transformers (BERT) model, a powerful Natural Language Processing (NLP) framework. The system ensures precise and personalized recommendations by understanding the semantic relationships within job descriptions and user profiles. The model integrates contextual matching of skills and preferences, addressing the limitations of traditiona
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Nikhil, Modi, Indalkar Aaditi, Kapole Aryan, Khamkar Saara, and A. Indalkar Madhavi. "Next-Gen Talent Matching System: Innovating Recruitment with AI-Driven JD and CV Matching." International Journal of Innovative Science and Research Technology (IJISRT) 9, no. 12 (2025): 2437–41. https://doi.org/10.5281/zenodo.14608655.

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This study introduces the Next-Gen Talent Matching System, an innovative JD-based CV filtering web application designed to transform the recruitment process by leveraging Large Language Models (LLMs) and OpenAI technologies. Unlike traditional systems that rely on skill-based c filtering, this system focuses on job description (JD)-based filtering, providing greater accuracy and relevance in candidate selection. By enabling users to securely submit CVs, the system stores data in a MongoDB database, allowing HR administrators to access and match CVs based on semantic analysis. Using LLMs, the s
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Dissertations / Theses on the topic "Job matching system"

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Gonard, François. "Cold-start recommendation : from Algorithm Portfolios to Job Applicant Matching." Thesis, Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLS121/document.

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La quantité d'informations, de produits et de relations potentielles dans les réseaux sociaux a rendu indispensable la mise à disposition de recommandations personnalisées. L'activité d'un utilisateur est enregistrée et utilisée par des systèmes de recommandation pour apprendre ses centres d'intérêt. Les recommandations sont également utiles lorsqu'estimer la pertinence d'un objet est complexe et repose sur l'expérience. L'apprentissage automatique offre d'excellents moyens de simuler l'expérience par l'emploi de grandes quantités de données.Cette thèse examine le démarrage à froid en recomman
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Chen, Po-Han, and 陳柏翰. "A Personalized On-line Job Matching Recommender System." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/78494543686618368659.

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碩士<br>中國文化大學<br>資訊管理研究所碩士在職專班<br>94<br>In recent years, due to development of on-line job matching systems, looking for a job is no longer limited to follow the traditional way of getting related information from newspapers and magazines. By providing rich kinds of information, the on-line job matching systems have attracted more and more of job seekers. The on-line job match-ing system are fast, convenient, and low cost, and offers function of publishing resumes and applying for job online which traditional job-finding service can not provide. How-ever, a huge and powerful database is then ne
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溫瑞烘. "A Study of Ontology-based Semantic Job Matching System." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/12555513588980536455.

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博士<br>國立臺灣師範大學<br>工業教育學系<br>96<br>The aim of the study was to develop different types of job matching systems based on Ontology Theory, human resource theory and system development theory. First, the study explored the literature related to Ontology to understand methodologies of ontology development. Then a pilot study was conducted to gather the skill requirements for software developers needed by current enterprises from human resource web sites nationwide and abroad. Based on the ontology development methodology and the result of the pilot study, an information competency ontology was buil
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Liao, Yi-Lin, and 廖翊伶. "Research on Usability Design of Job Seeking and Matching System." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/45994865727430809664.

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碩士<br>中原大學<br>資訊管理研究所<br>105<br>We hope to strengthen the interaction and contact between enterprises and students and alumni by e-platform service, and do provide employment and care services for students and alumni.Efficient integration of employment and career information from all sides, increase the students, alumni and business opportunities for job opportunities. This study will be set in the scope of the Chung Yuan Christian University job seeking and matching system,to the 中原人生涯關懷網 for the study of cases, to explore the use of the中原人生涯關懷網of the Chung Yuan Christian University students
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Jao, Jyuhn-Der, and 饒駿德. "Applying Conversational Recommender System to Online Job Banks Matching Mechanism." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/81566991069238321363.

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碩士<br>中國文化大學<br>資訊管理學系碩士在職專班<br>101<br>It is increasingly difficult to make effective use of Internet information, given the rapid growth in data volume and diversity. That is how the recommendation systems come into play in this field. Recommendation systems not only for helping people to choose products or services, but also reducing them the time spent in the searching in electronic commerce. With the rapid development of the Internet and information technology, many businesses and job seekers through the Internet such as online job banks, social networks as channel for jobs in the recent y
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pocheng-huang and 黃柏誠. "A Study On The Survey Of The Matching System Job Searching And People Recruiting." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/03741553228832885995.

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碩士<br>萬能科技大學<br>經營管理研究所<br>95<br>In the past tradition recruitment takes place through the publication in the media of newspapers and magazines. Nowadays due to the popularity of using computer especially internet network, human resources websites become a kind of new channel for matchmaking. No matter on job hunting or people recruiting, these offer multiple channels for matchmaking the two parties. The source of data in this study comes from VNU104 Website of Vanung University. In order to be more objective, the study is divided into three stages. In the first stage, telephone survey is
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Coelho, Andreia Pinto de Almeida. "Projecto de avaliação do ajustamento das competências adquiridas no sistema de aprendizagem." Master's thesis, 2010. http://hdl.handle.net/10071/4147.

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O projecto apresentado elabora um instrumento de avaliação do ajustamento de competências adquiridas no Sistema de Aprendizagem, permitindo responder as questões relacionadas com a concordância entre os conhecimentos e competências adquiridos pelos formandos deste sistema de formação e as competências requeridas e necessidades do mercado de trabalho. Através de uma metodologia de recolha de informações por questionários a ex-formandos, a empresas que participam na aprendizagem dos jovens e a empresas que não têm qualquer contacto com o processo formativo, com base numa metodologia da aut
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Pombo, José Luís Fava de Matos. "Landing on the right job : a machine learning approach to match candidates with jobs applying semantic embeddings." Master's thesis, 2019. http://hdl.handle.net/10362/60405.

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Project Work presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics<br>Job application’ screening is a challenging and time-consuming task to execute manually. For recruiting companies such as Landing.Jobs it poses constraints on the ability to scale the business. Some systems have been built for assisting recruiters screening applications but they tend to overlook the challenges related with natural language. On the other side, most people nowadays specially in the IT-sector use the Internet to look for jobs, however, given the huge amount
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Books on the topic "Job matching system"

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ABLE, OPERATION, and United States. Administration on Aging., eds. Maximatch, job matching computer system: Final report. Operation ABLE, Inc., 1988.

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ABLE, OPERATION, and United States. Administration on Aging., eds. Maximatch, job matching computer system: Final report. Operation ABLE, Inc., 1988.

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Lightfoot, Mary Ann. Off-line field test design for evaluating two approaches to person-job matching: The Army Recruit Quota System (REQUEST) and the Enlisted Personnel Allocation System (EPAS). U.S. Army Research Institute for the Behavioral and Social Sciences, 2003.

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Lightfoot, Mary Ann. Off-line field test design for evaluating two approaches to person-job matching: The Army Recruit Quota System (REQUEST) and the Enlisted Personnel Allocation System (EPAS). U.S. Army Research Institute for the Behavioral and Social Sciences, 2003.

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Lightfoot, Mary Ann. Off-line field test design for evaluating two approaches to person-job matching: The Army Recruit Quota System (REQUEST) and the Enlisted Personnel Allocation System (EPAS). U.S. Army Research Institute for the Behavioral and Social Sciences, 2003.

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Botterbusch, Karl F. A comparison of computerized job matching systems. Materials Development Center, Stout Vocational Rehabilitation Institute, School of Education and Human Services, University of Wisconsin-Stout, 1986.

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Lightfoot, Mary Ann. Matching recruits to jobs: Enlisted personnel allocation system. U.S. Army Research Institute for the Behavioral and Social Sciences, 2000.

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Lightfoot, Mary Ann. Matching recruits to jobs: The enlisted personnel allocation system. U.S. Army Research Institute for the Behavioral and Social Sciences, 2000.

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Off-Line Field Test Design for Evaluating Two Approaches to Person-Job Matching: The Army Recruit Quota System (REQUEST) and the Enlisted Personnel Allocation System (EPAS). Storming Media, 2003.

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Book chapters on the topic "Job matching system"

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Heap, Bradford, Alfred Krzywicki, Wayne Wobcke, Mike Bain, and Paul Compton. "Combining Career Progression and Profile Matching in a Job Recommender System." In Lecture Notes in Computer Science. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-13560-1_32.

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Cevik Onar, Sezi, Basar Oztaysi, and Cengiz Kahraman. "Hesitant Fuzzy Evaluation of System Requirements in Job Matching Platform Design." In Advances in Fuzzy Logic and Technology 2017. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-66827-7_5.

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Boukari, Shayma, and Rim Faiz. "BERTopic-LDA Model for a Bidirectional Recommendation System: Toward Matching Jobs and Job Seekers." In Proceedings of Ninth International Congress on Information and Communication Technology. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-3299-9_46.

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Thamrin, Geovanne Farell, Putra Jaya, Ahmaddul Hadi, and Sandi Rahmadika. "User Interface Analysis on Job Matching Information System Using Eight Golden Rules." In Advances in Social Science, Education and Humanities Research. Atlantis Press SARL, 2023. http://dx.doi.org/10.2991/978-2-38476-056-5_18.

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Shinkawa, Kaoru, Kenichi Saito, Masatomo Kobayashi, and Atsuhi Hiyama. "Towards Extracting Recruiters’ Tacit Knowledge Based on Interactions with a Job Matching System." In Human Aspects of IT for the Aged Population. Applications, Services and Contexts. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-58536-9_44.

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Giambona, Francesca, Adham Kahlawi, Lucia Buzzigoli, Laura Grassini, and Cristina Martelli. "Big data analysis and labour market: an analysis of Italian online job vacancies data." In Proceedings e report. Firenze University Press, 2021. http://dx.doi.org/10.36253/978-88-5518-461-8.22.

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Economists and social scientists are increasingly making use of web data to address socio-economic issues and to integrate existing sources of information. The data produced by online platforms and websites could produce a lot of useful and multidimensional information with a variety of potential applications in socio-economic analysis. In this respect, with the internet growth and knowledge, many aspects of job search have been transformed due to the availability of online tools for job searching, candidate searching and job matching. In European countries there is growing interest in designi
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Yokota, Takuya, and Yuri Nakao. "Towards Multi-stakeholder Evaluation of ML Models: A Crowdsourcing Study on Metric Preferences in Job-Matching System." In Communications in Computer and Information Science. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-82633-7_8.

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Stalidis, George, and Selini Kyriazidou. "Job Role Description and Skill Matching in a Rapidly Changing Labor Market Using Knowledge Engineering." In Strategic Innovative Marketing and Tourism. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-51038-0_21.

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AbstractThe job market is continuously evolving and suffers from skill mismatch, while digital platforms for job seeking, human resource management and training planning are widely adopting intelligent matching engines. Efficient job description and successful skill matching require standard terminologies for job positions and their requirements/qualifications, such as the ‘European Skills, Competences, Qualifications and Occupations’ (ESCO). The aim of this paper is to search whether ESCO—as the most representative job-related information model—has been adopted in the current rapidly evolving
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Fu, Bin, Hongzhi Liu, Yao Zhu, Yang Song, Tao Zhang, and Zhonghai Wu. "Beyond Matching: Modeling Two-Sided Multi-Behavioral Sequences for Dynamic Person-Job Fit." In Database Systems for Advanced Applications. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-73197-7_24.

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Jain, Lorick, M. A. Harsha Vardhan, Ganesh Kathiresan, and Ananth Narayan. "Optimizing People Sourcing Through Semantic Matching of Job Description Documents and Candidate Profile Using Improved Topic Modelling Techniques." In Advances in Intelligent Systems and Computing. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-3514-7_66.

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Conference papers on the topic "Job matching system"

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Bhavana, D. E., Avvari Venkatesh, Sanjana Kumar, M. D. Amrutha, Mohammed Muzamil Husssen, and I. V. Chaitra. "ML-Based Job Matching and Skill Development Recommendation System." In 2025 International Conference on Knowledge Engineering and Communication Systems (ICKECS). IEEE, 2025. https://doi.org/10.1109/ickecs65700.2025.11035278.

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Xiuyun, Zhu, and Yang Hualing. "Optimizing Job Matching Efficiency: A Novel Employment Information System Algorithm." In 2024 International Conference on Computers, Information Processing and Advanced Education (CIPAE). IEEE, 2024. https://doi.org/10.1109/cipae64326.2024.00134.

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Kumar, Priyan Malarvizhi, Punit Joshi, Utkarsh Dubey, Akshat Srivastava, and Balasubramanian Prabhu Kavin. "Enhanced Job Recommendation System Using Skill Based Rule Matching Algorithm." In 2025 International Conference on Data Science and Business Systems (ICDSBS). IEEE, 2025. https://doi.org/10.1109/icdsbs63635.2025.11031850.

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Gautam, Geetesh, Dolly Sharma, and Vijit Chaturvedi. "Automating Talent Acquisition Assisted by Resume Parsing System for Enhanced Job Matching." In 2025 2nd International Conference on Computational Intelligence, Communication Technology and Networking (CICTN). IEEE, 2025. https://doi.org/10.1109/cictn64563.2025.10932337.

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Soni, Vibha. "AI in Job Matching and Recruitment: Analyzing the Efficiency and Equity of Automated Hiring Processes." In 2024 International Conference on Knowledge Engineering and Communication Systems (ICKECS). IEEE, 2024. http://dx.doi.org/10.1109/ickecs61492.2024.10617325.

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Pawade, Dipti, Tanuj Joshi, and Siddhesh Parkhe. "Survey on Resume and Job Profile Matching System." In 2023 6th International Conference on Advances in Science and Technology (ICAST). IEEE, 2023. http://dx.doi.org/10.1109/icast59062.2023.10454929.

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Chen, Yue, and Qi Xu. "Measuring transit job accessibility considering the matching between jobs and workers in Beijing." In 5th International Conference on Traffic Engineering and Transportation System (ICTETS 2021), edited by Yongkang Xing. SPIE, 2021. http://dx.doi.org/10.1117/12.2620234.

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Mohamed, Ramesh Kumar Moona Haji. "Investigation Of Technology Acceptance And Adoption Of E-Government Job Matching System." In AIMC 2018 - Asia International Multidisciplinary Conference. Cognitive-Crcs, 2019. http://dx.doi.org/10.15405/epsbs.2019.05.02.5.

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Gaddam, Jyotheesh, Jan Carlo Barca, Thanh Thi Nguven, and Maia Angelova. "Job-Profile Matching with CTN and MADRL with GEABB: A Recommender System." In 2024 16th International Conference on Computer and Automation Engineering (ICCAE). IEEE, 2024. http://dx.doi.org/10.1109/iccae59995.2024.10569707.

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Pendyala, Vishnu, Nishtha Atrey, Tina Aggarwal, and Saumya Goyal. "Artificial Intelligence Enabled, Social Media Leveraging Job Matching System for Employers and Applicants." In 2022 International Conference on Recent Trends in Microelectronics, Automation, Computing and Communications Systems (ICMACC). IEEE, 2022. http://dx.doi.org/10.1109/icmacc54824.2022.10093323.

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Reports on the topic "Job matching system"

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Flabbi, Luca, Matteo Bobba, and Santiago Levy Algazi. Labor Market Search, Informality and Schooling Investments. Inter-American Development Bank, 2018. http://dx.doi.org/10.18235/0011813.

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This paper develops a search and matching model where firms and workers are allowed to form matches (jobs) that can be formal or informal. Workers optimally choose the level of schooling acquired before entering the labor market and whether to search for a job as unemployed or as self-employed. Firms optimally decide the formality status of the job and bargain with workers over wages. The resulting equilibrium size of the informal sector is an endogenous function of labor market parameters and institutions. The paper focuses on an increasingly important institution: a “dual” social protection
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Bosch, Mariano, and Julen Esteban-Pretel. Labor Market Effects of Introducing Unemployment Benefits in an Economy with High Informality. Inter-American Development Bank, 2013. http://dx.doi.org/10.18235/0011471.

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Unemployment benefit systems are nonexistent in many developing economies. Introducing such systems poses many challenges, which are partly due to the high level of informality in the labor markets of these economies. This paper studies the consequences on the labor market of implementing an unemployment benefit system in economies with large informal sectors and high flows of workers between formality and informality. We build a search and matching model with endogenous destruction, on-the-job search, and intersectoral flows, where agents in the economy decide optimally whether or not to form
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Lightfoot, Mary A., and Peter F. Ramsberger. Matching Recruits to Jobs: The Enlisted Personnel Allocation System. Defense Technical Information Center, 2000. http://dx.doi.org/10.21236/ada382909.

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Jiang, Yi, Liming Chen, and Eugenia Go. Accessibility Analysis of the South Commuter Railway Project of the Philippines. Asian Development Bank, 2021. http://dx.doi.org/10.22617/brf2101314-2.

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This brief outlines findings on how the 54.6 km South Commuter Railway (SCR) to be built between Metro Manila and Laguna province in the Philippines is expected to improve access to jobs. A quantitative analysis estimates that residents of cities and municipalities with an SCR station will be able to reach an average of 300,000 extra jobs within a 1-hour commute—an increase of 15.3% in the south and 8.5% in Metro Manila. This could lead to better labor market matching, higher income for workers and more job opportunities for low-income households. The study contributes to efforts to quantify t
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Franken, Swetlana, Lotte Prädikow, and Nina Mauritz. Künstliche Intelligenz in der Personalbeschaffung - Chancen, Herausforderungen und Handlungsempfehlungen. Kompetenzzentrum Arbeitswelt.Plus, 2022. http://dx.doi.org/10.55594/pojc9826.

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Künstliche Intelligenz (KI) erhält Einzug in immer mehr Unternehmensbereiche und es ist davon auszugehen, dass die Nutzung intelligenter Algorithmen und KI-Methoden auch die Arbeit im HR-Bereich stark verändern wird. Dabei ergeben sich aus den bereits existierenden digitalen Systemen im Personalwesen viele Anknüpfungspunkte für den Einsatz intelligenter, algorithmischer Systeme, insbesondere im Prozess der Personalbeschaffung. Dennoch sind solche KI-Anwendungen in der Unternehmenspraxis noch nicht sehr weit verbreitet. Das vorliegende Paper möchte Unternehmen dabei unterstützen, folgende Frage
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