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Journal articles on the topic 'Job matching system'

Author: Grafiati

Published: 7 June 2025

Last updated: 2 August 2025

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1

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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Kumari, Sneha. "Job Recommendation System Using NLP." International Journal for Research in Applied Science and Engineering Technology 11, no. 5 (2023): 2721–28. http://dx.doi.org/10.22214/ijraset.2023.52183.

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Abstract: Recommender systems is one of the most successful machine learning applications. We are exposed to the products/information recommended by these systems everywhere in our daily life. This project will introduce several recommender systems in NLP, specifically in the domain of online recruitment. I will explain the important ideas behind the recommender systems in our web application, it might be also similar with those in recruiting platforms like LinkedIn, Xing. One of my main jobs is to design and develop recommender systems on the skill-based matching app. Before getting into this

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Drigas, A., S. Kouremenos, S. Vrettos, J. Vrettaros, and D. Kouremenos. "An expert system for job matching of the unemployed." Expert Systems with Applications 26, no. 2 (2004): 217–24. http://dx.doi.org/10.1016/s0957-4174(03)00136-2.

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Alsaif, Suleiman Ali, Minyar Sassi Hidri, Imen Ferjani, Hassan Ahmed Eleraky, and Adel Hidri. "NLP-Based Bi-Directional Recommendation System: Towards Recommending Jobs to Job Seekers and Resumes to Recruiters." Big Data and Cognitive Computing 6, no. 4 (2022): 147. http://dx.doi.org/10.3390/bdcc6040147.

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For more than ten years, online job boards have provided their services to both job seekers and employers who want to hire potential candidates. The provided services are generally based on traditional information retrieval techniques, which may not be appropriate for both job seekers and employers. The reason is that the number of produced results for job seekers may be enormous. Therefore, they are required to spend time reading and reviewing their finding criteria. Reciprocally, recruitment is a crucial process for every organization. Identifying potential candidates and matching them with

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Kim, Seongchan, Jincheul Jang, Seong Jung Kim, Hyojin Chin, and Mun Yong Yi. "Job Preference Analysis and Job Matching System Development for the Middle Aged Class." Journal of Intelligence and Information Systems 22, no. 4 (2016): 247–64. http://dx.doi.org/10.13088/jiis.2016.22.4.247.

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Ugale, Archana V. "Resume Clustering and Job Description Matching." International Journal for Research in Applied Science and Engineering Technology 13, no. 4 (2025): 2881–87. https://doi.org/10.22214/ijraset.2025.68831.

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The efficient functioning of drainage systems is critical for urban infrastructure, playing a key role in managing stormwater, preventing flooding, and safeguarding public health and safety. ABSTRACT: In today’s competitive job market, both job seekers and employers are increasingly turning to automated systems to improve the efficiency of the hiring process. This paper explores Resume Clustering and Job Description Matching, two key aspects of recruitment technology, which are designed to facilitate faster, more accurate hiring decisions. We propose a methodology for automatically matching re

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Chormule, Amit. "Job Portal." International Scientific Journal of Engineering and Management 04, no. 06 (2025): 1–9. https://doi.org/10.55041/isjem04688.

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The digital transformation of recruitment has necessitated the development of intelligent, user-centric platforms to bridge the gap between job seekers and employers. This paper presents the design and implementation of a web-based Job Portal System built using the MERN (MongoDB, Express.js, React.js, Node.js) stack. The system enables job seekers to register, create profiles, upload resumes, and apply for jobs, while employers can post job openings, view applications, and manage the recruitment process. The platform includes core functionalities such as secure user authentication, role-based

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Mulay, Aneesh, Shriyash Sutar, Jiten Patel, Aditi Chhabria, and Snehal Mumbaikar. "Job Recommendation System Using Hybrid Filtering." ITM Web of Conferences 44 (2022): 02002. http://dx.doi.org/10.1051/itmconf/20224402002.

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As for today’s era, recruitment can be considered as one of most difficult process to undergo for job seeking candidate. Many fresher candidates face issue while job recruitment process to undergo which field of interest. The proposed system will help the user to overcome this difficulties by matching their work experience, skills and other details with appropriate companies suitable for respective user. The system will also help experienced users in getting their intended job on the basis of their last job profile. The job recommendation algorithm developed is tedious nor complicated and will

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Sharmila, G.K, P.Mehataj, Pallavi.U, Reddy M.Arunkumar, and H.K Raviteja. "AI Powered Job Recommendation and Skill Enhancement System." Journal of Scholastic Engineering Science and Management (JSESM), A Peer Reviewed Universities Refereed Multidisciplinary Research Journal 4, no. 3 (2025): 45–48. https://doi.org/10.5281/zenodo.15058401.

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In today’s rapidly evolving job market, finding the right job and enhancing relevant skills are crucial for career growth. This paper presents an AI-powered Job Recommendation and Skill Enhancement System designed to help job seekers find the most suitable job opportunities based on their qualifications, experience, and preferences while simultaneously recommending skill enhancement resources to increase employability. The system leverages machine learning algorithms and natural language processing (NLP) to analyze user profiles, job descriptions, and market trends. A recommendation engi

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Priyanka Singla. "An Intelligent Job Recommendation System based on Semantic Embeddings and Machine Learning." Journal of Information Systems Engineering and Management 10, no. 5s (2025): 520–42. https://doi.org/10.52783/jisem.v10i5s.681.

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To address the shortcomings in existing approaches of job recommendation systems, this paper proposes a novel machine-learning-based job recommendation system that performs bi-directional matching for dynamic and accurate recommendations. The proposed approach generates ideal job recommendations for a targeted Curriculum Vitae (CV) and vice versa. Unlike previous approaches, the proposed approach incorporates natural language processing (NLP) techniques to extract linguistic features such as Bag of Words (BoW), n-grams, TF-IDF, and Parts-of-Speech (PoS) tag and build a rich feature set. These

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Kamaruddin, Norhaslinda, Abdul Wahab Abdul Rahman, and Ramizah Amirah Mohd Lawi. "Jobseeker-industry matching system using automated keyword selection and visualization approach." Indonesian Journal of Electrical Engineering and Computer Science 13, no. 3 (2019): 1124. http://dx.doi.org/10.11591/ijeecs.v13.i3.pp1124-1129.

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Learning opportunities are available with the accessibility of new learning technologies, discovery of untraditional learning pathways and awareness of the importance of connecting current knowledge with new learning. Such situation allows the expansion in the number of courses, programs and professional certifications offered to the students resulting to the increment of the number of graduates annually. The graduates then employed by the industry for executing the job. However, there is a growing concern about the increment of unemployed graduates in the job market. One of the reasons of the

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Darni, Resmi, and Lativa Mursyida. "Expert System Karir Terpadu Berbasis Personality dalam Implementasi Job Matching." JTEV (Jurnal Teknik Elektro dan Vokasional) 8, no. 2 (2022): 317. http://dx.doi.org/10.24036/jtev.v8i2.116671.

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Belum optimalnya penyerapan lulusan SMK ke dunia kerja dan industri menjadi fokus utama penelitian ini, salah satu faktor penyebab ketidak optimalan penyerapan lulusan SMK tersebut adalah belum terintegrasinya sistem informasi karir yang ada dengan kebutuhan dunia kerja, sehingga data dan informasi yang diperoleh menjadi tidak valid, praktis dan efektif. Penelitian ini bertujuan untuk menjelaskan proses perancangan sistem pakar karir terintegrasi yang mampu merekomendasikan karir dan pekerjaan berdasarkan kepribadian. Metode yang digunakan dalam penelitian ini adalah metode 4D yaitu Define, De

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Sukwadi, Ronald, Vivi Triyanti, Alexander Arya Sangkara, and Arum Park. "Enhancing Career Fit : A Big Data-driven “Job Matching” System." Asia Pacific Journal of Information Systems 34, no. 4 (2024): 1004–24. https://doi.org/10.14329/apjis.2024.34.4.1004.

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Karhale, Prof Shivani. "Resume Analysis System Using Natural Language Processing." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 06 (2025): 1–9. https://doi.org/10.55041/ijsrem49872.

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Abstract : In the era of digital recruitment, organizations face the challenge of processing thousands of resumes efficiently and accurately. Manual resume screening is not only time-consuming but also prone to human error and bias. To address these issues, this project presents a Resume Analysis System using Natural Language Processing (NLP), which automates the process of analyzing and filtering resumes based on job requirements. The system leverages advanced NLP techniques such as tokenization, part-of-speech tagging, named entity recognition, and TF-IDF (Term Frequency-Inverse Document Fre

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Craiger, J. Philip, Michael D. Coovert, and Mark S. Teachout. "Predicting Job Performance with a Fuzzy Rule-Based System." International Journal of Information Technology & Decision Making 02, no. 03 (2003): 425–44. http://dx.doi.org/10.1142/s0219622003000744.

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Classification problems affect all organizations. Important decisions affecting an organization's effectiveness include predicting the success of job applicants and the matching and assignment of individuals from a pool of applicants to available positions. In these situations, linear mathematical models are employed to optimize the allocation of an organization's human resources.Use of linear techniques may be problematic, however, when relationships between predictor and criterion are nonlinear. As an alternative, we developed a fuzzy associative memory (FAM: a rule-based system based on fuz

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Norhaslinda, Kamaruddin, Wahab Abdul Rahman Abdul, and Amirah Mohd Lawi Ramizah. "Jobseeker-industry matching system using automated keyword selection and visualization approach." Indonesian Journal of Electrical Engineering and Computer Science 13, no. 3 (2019): 1124–29. https://doi.org/10.11591/ijeecs.v13.i3.pp1124-1129.

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Learning opportunities are available with the accessibility of new learning technologies, discovery of untraditional learning pathways and awareness of the importance of connecting current knowledge with new learning. Such situation allows the expansion in the number of courses, programs and professional certifications offered to the students resulting to the increment of the number of graduates annually. The graduates then employed by the industry for executing the job. However, there is a growing concern about the increment of unemployed graduates in the job market. One of the reasons of the

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B, Mr Sandeep. "JobOrbit-Intelligent Recruitment System." International Journal for Research in Applied Science and Engineering Technology 12, no. 12 (2024): 1128–31. https://doi.org/10.22214/ijraset.2024.66001.

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This project focuses on developing an Intelligent Recruitment System leveraging advanced machine learning techniques to revolutionize the recruitment process. The system automates key tasks, such as analyzing resumes, extracting essential details, and matching candidate profiles with job requirements. By employing algorithms for natural language processing (NLP) and predictive analytics, the system evaluates a candidate's suitability for specific roles based on their skills, experience, and qualifications. Additionally, it offers tailored job recommendations to candidates, enhancing their job

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Juhi, Dhameliya, and Desai Nikita. "Job Recommendation System using Content and Collaborative Filtering Based Techniques." International Journal of Soft Computing and Engineering (IJSCE) 9, no. 3 (2019): 8–13. https://doi.org/10.35940/ijsce.C3266.099319.

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Internet based recruiting platforms decrease advertisement cost, but they suffer from information overload problem. The job recommendation systems (JRS) have achieved success in e-recruitment process but still they are not able to capture the complexity of matching between candidates’ desires and organizations’ requirements. Thus, we propose a hybrid JRS which combines recommendations of content-based filtering (CBF) and collaborative filtering (CF) to overcome their individual major shortcomings namely overspecialization and over-fitting. In proposed system, CBF model makes recomm

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Pitrasacha and Eka Arriyanti. "Desain dan Implementasi Job Matching System Menggunakan Metode Kombinasi WSM-TOPSIS." METIK JURNAL 4, no. 2 (2020): 1–9. http://dx.doi.org/10.47002/metik.v4i2.180.

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Penelitian ini dilakukan untuk mendesain dan mengimplementasikan sebuah job matching system sebagai fasilitator antara lulusan perguruan tinggi yang mencari kerja dan penyedia kerja. Sistem berkerja dengan melakukan pencocokan antara kebutuhan dan spesifikasi tenaga kerja dari penyedia kerja dengan profil kompetensi lulusan perguruan tinggi. Studi kasus penelitian dilakukan di STMIK WICIDA. Metode kombinasi antara weighted scoring model (WSM) dan Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) digunakan untuk meningkatkan akurasi hasil pencocokan. Target khusus dari dar

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Sanyal, Kaustav. "Intelligent Resume Parsing and Job Recommendation via Web-Based CV Analysis System." International Journal for Research in Applied Science and Engineering Technology 13, no. 5 (2025): 2291–300. https://doi.org/10.22214/ijraset.2025.70746.

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The process of matching job applicants to suitable job openings is typically inefficient due to unorganized resume formats and absence of customized job search facilities. This paper presents a light-weight web-based system that automatically extracts structured information from PDF resumes and recommends suitable job openings based on publicly available job search APIs. The system is based on natural language processing-based data extraction, stores the extracted information in a CSV database, and builds context-sensitive job queries. A basic web interface built on top of Flask supports PDF u

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Sarsenbay, Shakhmar, Asset Kabdiyev, Iraklis Varlamis, et al. "Generating Job Recommendations Based on User Personality and Gallup Tests." Algorithms 18, no. 5 (2025): 275. https://doi.org/10.3390/a18050275.

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This paper introduces a novel approach to job recommendation systems by incorporating personality traits evaluated through the Gallup CliftonStrengths assessment, aiming to enhance the traditional matching process beyond skills and qualifications. Unlike broad models like the Big Five, Gallup’s CliftonStrengths assesses 34 specific talents (e.g., ‘Analytical’, ‘Empathy’), enabling finer-grained, actionable job matches. While existing systems focus primarily on hard skills, this paper argues that personality traits—such as those measured by the Gallup test—play a crucial role in determining car

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Sciulli, Dario, and Antonio Gomes de Menezes. "The Performance of Portuguese Job-centers." Ekonomiaz. Revista vasca de Economía 93, no. 1 (2018): 108–33. https://doi.org/10.69810/ekz.1285.

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This paper analyzes the performance of the country-wide system of 86 job-centers in Portugal, which have the public mandate of matching unemployed individuals with vacancies. The paper uses a rich micro dataset for the years 1998-2002 which allows the construction of individual unemployment duration spells and subsequent employment outcomes, while observing individual characteristics such as age, education, gender and past job experiences and other labour-market variables defined at the local-labour market or jobcenter level. Among the several conclusions and policy recommendations, it should

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Mangesh, Kumar Yadav. "Online Job Portal using Django." International Journal of Innovative Science and Modern Engineering (IJISME) 12, no. 1 (2024): 1–4. https://doi.org/10.35940/ijisme.K1307.12010124.

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<strong>Abstract:</strong> The main purpose of the job portal of the Django project is to manage job information, search, post jobs, register with employers, and find jobs. It manages all information regarding employers, interviews, job searches, and workplaces. The project was created with the administration closed, so it was easier for administrators to control it. The startup aims to create the necessary software to reduce the hassle of negotiations with employers, cover letters, interviews, and career guidance. It tracks all information regarding job postings, job listings, and job searche

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Lolage, Gauri S. "Online Job Portal With Resume Parsing and Matching." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 06 (2025): 1–9. https://doi.org/10.55041/ijsrem50122.

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Abstract - Campus placements often demand significant manual effort, from matching student profiles to job requirements to tracking application statuses. This process is transformed with the Training and Placement Officer (TPO) portal, built using the MERN stack and AI-powered resume parsing. The portal automates candidate shortlisting by analyzing resumes and ensuring at least a 50% skill match with job descriptions, significantly reducing TPO workloads. Job postings created by TPOs are instantly visible on student dashboards, with automated email notifications keeping students updated and en

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Zou, Zhou, Sharin Hazlin Huspi, Ahmad Najmi Amerhaider Nuar, and Kebiao Zhu. "A Conceptual Framework of Career Move Recommendation System." Journal of Advanced Research Design 126, no. 1 (2025): 91–98. https://doi.org/10.37934/ard.126.1.9198.

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Nowadays, job recommendation systems are becoming more and more popular for job seekers to generate personalized job recommendations, but it is increasingly challenging as the techniques used are changing rapidly. Most of the existing job recommendation systems only consider the user’s interests, without consideration of the user’s skills, which can help them to make a career move. In this paper, the problem was addressed by applying the Design Science Research Methodology to propose an artefact. The proposed conceptual framework generates personalized job and skill recommendations for a caree

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Barrera Guale, Edison Fernando, Nallely Estefanía Pastuña Ayala, and Jaime Mesías Cajas. "Development of an integrated labor management system with ai, voice commands, and chatbot for Mega Ferretería Bonilla." Revista Multidisciplinar de Estudios Generales 4, no. 3 (2025): 360–81. https://doi.org/10.70577/reg.v4i3.176.

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This research aims to develop an integrated employment and job-matching management system for the company Mega Ferretería Bonilla, incorporating emerging technologies such as artificial intelligence, voice commands, and a chatbot. The project addresses the need to modernize personnel selection processes, which previously showed delays, low accuracy in profile matching, and operational overload in the human resources department. To achieve this, an agile development methodology combined with a mixed research approach was adopted. Functional modules were designed to allow user registration, job

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Siddesh, G. M., and K. G. Srinisas. "An Adaptive Scheduler Framework for Complex Workflow Jobs on Grid Systems." International Journal of Distributed Systems and Technologies 3, no. 4 (2012): 63–79. http://dx.doi.org/10.4018/jdst.2012100106.

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Grid Computing provides sharing of geographically distributed resources among large scale complex applications. Due to dynamic nature of resources in grid, there is a need of highly efficient job scheduling and resource management policies in grid. A novel Grid Resource Scheduler (GRS) is proposed to effectively utilize the available resources in Grid. Proposed GRS contributes, an optimal job scheduling algorithm on Job Rank-Backfilling policy and a resource matching algorithm based on ranking of resources with best fit allocation model. Performance of GRS is measured by considering a web base

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Karunamurthy, Dr A. "AI-Powered Resume Analysis Using SpaCy for Skill Extraction and Job Matching." International Scientific Journal of Engineering and Management 04, no. 05 (2025): 1–7. https://doi.org/10.55041/isjem03528.

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Abstract -In today's competitive job market, recruiters face the challenge of efficiently sifting through vast volumes of resumes to identify the best candidates for open positions. Traditional keyword-based filtering methods are often inadequate in identifying the nuances of skills and experiences required for specific job roles. This project presents an AI-powered resume analysis system using the SpaCy natural language processing (NLP) library to enhance the accuracy of resume screening and job matching. Leveraging SpaCy's advanced capabilities, including Named Entity Recognition (NER), sema

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Fernández-Reyes, Francis C., and Suraj Shinde. "CV Retrieval System based on job description matching using hybrid word embeddings." Computer Speech & Language 56 (July 2019): 73–79. http://dx.doi.org/10.1016/j.csl.2019.01.003.

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Tsang, Hector W. H., Pi-Fan Chiu, and Bacon F. L. Ng. "An end user survey on the development of an on-line job information system for people with psychiatric disabilities in Hong Kong." Journal of Vocational Rehabilitation 17, no. 1 (2002): 33–38. http://dx.doi.org/10.3233/jvr-2002-00140.

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An on-line job information system facilitating the vocational rehabilitation process for use by rehabilitation professionals, people with psychiatric disabilities, and their relatives are to be developed in Hong Kong. The preferred functions and features of the system were collected by a questionnaire survey among 90 occupational therapists, social workers, and nurses as the potential end users. The preferred functions included job matching, providing information on job vacancies relevant to people with psychiatric disabilities, and making suggestions on areas of improvement on clients'abiliti

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Isernhagen, Susan J. "Job matching and return to work: Occupational rehabilitation as the link." WORK: A Journal of Prevention, Assessment & Rehabilitation 26, no. 3 (2006): 237–42. https://doi.org/10.3233/wor-2006-00516.

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Return to work after injury or illness is important for the worker and the employer. Medical providers manage and treat the worker with the illness or injury. Except in cases of focused specialists, the medical professional's role is to take care of a patient, rather than empower a worker. As much as there is promotion of the workers compensation health care system to be similar to sports medicine, there are significant dissimilarities. One major barrier is that the medical caregivers do not know the demands of jobs as they would know the details of sports. Thus, there is a gap in returning a

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Baali, Safia. "Recommendation System." International Journal of Artificial Intelligence and Machine Learning 11, no. 2 (2021): 1–14. http://dx.doi.org/10.4018/ijaiml.20210701.oa11.

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The most challenging problem in human resources specially in the IT digital services company, is to assign the best collaborator’s in the adequate project , then ensure the delivery’s performance.in this paper we aim to develop à recommandation System using based-content and collaborative filtering in order to recommend potential profiles for a new job offer. The Principal parts of this recommandation is the matching between job offer of new project and collaborators profiles and the scoring using AHP method. In the first step we propose a model of criteria to measure collective skills , we va

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Jung, Sunggwang, and Jaehyung Cho. "The Relationship Of NCS-Based Job Matching System Service Attributes, Satisfaction And Using Intention: The Moderating Effect of User Innovativeness." Restaurant Business 118, no. 3 (2019): 189–201. http://dx.doi.org/10.26643/rb.v118i3.7989.

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The reasons for the unemployment include the change in the economic structure and economy and the slump in job creation resulting from the shift of the industrial structure to high value-added industries. Therefore, the purpose of this study is to analyze the overall satisfaction of the NCS-based job matching system.

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Sabitha, K., and P. Jayaprakash. "Real-Time Manpower Hiring Platform for Service-Based Jobs." Research & Reviews: Journal of Internet & Networking 1, no. 2 (2025): 22–29. https://doi.org/10.5281/zenodo.15589942.

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<em>JOB_DESK is a cross-platform, real-time manpower hiring application designed for service-based jobs of all scales in Tamil Nadu. The platform connects local job providers—including event organizers, caterers, decorators, and logistics coordinators—with nearby job seekers interested in short-term, part-time, or on-demand work. Built using Flutter and Firebase, JOB_DESK ensures seamless operation across Android, iOS, and web platforms, featuring dynamic data handling and secure user authentication. Job providers can post detailed listings specifying job type, location, salary, an

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Ezugwu, Absalom E., Nneoma A. Okoroafor, Seyed M. Buhari, Marc E. Frincu, and Sahalu B. Junaidu. "Grid Resource Allocation with Genetic Algorithm Using Population Based on Multisets." Journal of Intelligent Systems 26, no. 1 (2017): 169–84. http://dx.doi.org/10.1515/jisys-2015-0089.

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AbstractThe operational efficacy of the grid computing system depends mainly on the proper management of grid resources to carry out the various jobs that users send to the grid. The paper explores an alternative way of efficiently searching, matching, and allocating distributed grid resources to jobs in such a way that the resource demand of each grid user job is met. A proposal of resource selection method that is based on the concept of genetic algorithm (GA) using populations based on multisets is made. Furthermore, the paper presents a hybrid GA-based scheduling framework that efficiently

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Jung, Sunggwang, Jae Hyung Cho, and IL-Woon Kim. "Corporations' and Job Seekers' Using Intention and WOM (Word-of-Mouth) of NCS-based Job Matching System." Advances in Economics and Business 7, no. 5 (2019): 194–201. http://dx.doi.org/10.13189/aeb.2019.070503.

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Yen, Thomas Y., and Robert G. Radwin. "Automated Job Analysis Using Biomechanical Data and Template Matching." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 41, no. 1 (1997): 712–16. http://dx.doi.org/10.1177/1071181397041001156.

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Spectral analysis of upper limb kinematic measurements has been previously demonstrated useful for quantifying physical stress properties of repetitive motion. The method requires manually separating the data into segments corresponding to individual tasks or work elements and computing power spectra. This study investigated using signal pattern recognition to help automate the analysis by separating the data through identification of stereotypical patterns in cyclical tasks. Joint angular data was collected for five industrial jobs using electrogoniometers attached to the wrist, elbow and sho

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Samruddhi, Farsole Sagar Darne Kunal Barahate Vaishnavi Bhute Rhutik Khode Minal Pazare Prof. R. V. Chaudhari. "Modern Real - Time Resume Analysis and Job Suggestion System Using NLP and Machine Learning Algorithm." International Journal of Advanced Innovative Technology in Engineering 10, no. 2 (2025): 134–37. https://doi.org/10.5281/zenodo.15422895.

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This paper is about in today's highly competitive job market job seekers face significant challenges in optimizing their resumes to pass Applicant Tracking Systems (ATS) and align with job requirements. Many resumes are rejected due to missing keywords, improper formatting, or a lack of ATS-friendly structures, making it difficult for qualified candidates to secure interviews. To address this issue, we present an AI-powered resume analysis system that enhances job matching efficiency by leveraging natural language processing (NLP) and machine learning. This system extracts key skills, qualific

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Patacsil, Frederick F., and Michael Acosta. "Analyzing the relationship between information technology jobs advertised on-line and skills requirements using association rules." Bulletin of Electrical Engineering and Informatics 10, no. 5 (2021): 2771–79. http://dx.doi.org/10.11591/eei.v10i5.2590.

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Online job vacancy sites have become an important source of information about the characteristics of labor market demand. It has become an avenue for job matching by both employers and employees and to study and analyze the labor market. This study proposed a methodology for identifying and analyzing skill-job relationships using frequency word occurrences of skills as a requirement of the job. It employed association rule mining which aims to discover frequent patterns, relationships among a set of items in the database. It collected published job vacancy data to IT job and skills requirement

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Xiang, Shou Bing, Jie Guo, Bo Zhong Ben, Guangwe Luo, and Zhong Wei. "Curriculum System Development and Practice Based on the 1221 Talent Training Model." Advanced Materials Research 271-273 (July 2011): 1578–83. http://dx.doi.org/10.4028/www.scientific.net/amr.271-273.1578.

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With in-depth analysis of the1221 talent training model and the case study of the major of electronic information engineering technology, the curriculum system development approach has been proposed based on the professional job standards and talent training quality requirements, so as to tackle the problems of vocational college graduates such as lack of practical skills and slow adaption to jobs. In accordance with the Two Main Lines of basic theoretical courses and practical skill courses, the approach has been designed systematically with integration of the Two Main Lines, providing all-ar

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Vanetik, Natalia, and Genady Kogan. "Job Vacancy Ranking with Sentence Embeddings, Keywords, and Named Entities." Information 14, no. 8 (2023): 468. http://dx.doi.org/10.3390/info14080468.

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Resume matching is the process of comparing a candidate’s curriculum vitae (CV) or resume with a job description or a set of employment requirements. The objective of this procedure is to assess the degree to which a candidate’s skills, qualifications, experience, and other relevant attributes align with the demands of the position. Some employment courses guide applicants in identifying the key requirements within a job description and tailoring their experience to highlight these aspects. Conversely, human resources (HR) specialists are trained to extract critical information from numerous s

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