Multivariate and Multicriteria Evaluation of Labour Market Situation

Nowadays the analysts of labour markets have a lot of different data and indicators that can be used for the evaluation of the labour market and monitor its development. But such a great number of monitoring determinants can create problems both with the evaluation and with the description of the situation of the labour market. Thus it is necessary to select a limited number of important indicators. A tool that can help with the selection of these indicators is a method of multidimensional statistics – multivariate analysis. In some cases it is necessary to use only one complex indicator that can evaluate the labour market from a lot of aspects. For a solution we can use multicriteria evaluation. These methods are described in this paper. We recommend a procedure for the in-depth study of the labour market situation.Labour Market, GIS, Factor Analysis, Multicriteria Evaluation

Technical and User-Oriented Prerequisites for Video CV Web-Based Recruitment Platform

Youth unemployment tends to be higher than in other age groups mainly because young people represent an inexperienced labour force. Some authors also believe it is due to an inability to match the qualified workforce to vacant positions. The importance of enabling young people to participate equally in the labour market is of the essence for economic growth. One of the attempts to tackle this issue was addressed through the Erasmus+ project CUVID, aimed at providing young people a way to present themselves in video-based form. This paper analyses quality standards for video CV platforms. For this purpose, 19 expert interviews with HR managers were conducted to identify their expectations towards video CVs. Based on the analysis of expert interviews, a recommendations summary with technical and user-oriented prerequisites was created, along with requirements and a transferability model for video CVs in the form of the CUVID platform

A Novel Approach for Learning How to Automatically Match Job Offers and Candidate Profiles

Automatic matching of job offers and job candidates is a major problem for a number of organizations and job applicants that if it were successfully addressed could have a positive impact in many countries around the world. In this context, it is widely accepted that semi-automatic matching algorithms between job and candidate profiles would provide a vital technology for making the recruitment processes faster, more accurate and transparent. In this work, we present our research towards achieving a realistic matching approach for satisfactorily addressing this challenge. This novel approach relies on a matching learning solution aiming to learn from past solved cases in order to accurately predict the results in new situations. An empirical study shows us that our approach is able to beat solutions with no learning capabilities by a wide margin.Comment: 15 pages, 6 figure

CurEval - Curriculum Evaluation

Efficiently screening and evaluating curricula in recruitment processes is a critical task that often requires substantial time and effort from Human Resources professionals. This work presents CurEval, an algorithm developed to automate the evaluation and screening of curricula based on vacancy requirements. The algorithm utilizes a predefined set of keywords and a CSV file format for input, facilitating easy data structuring and processing. To validate the algorithm’s performance and address privacy concerns, synthetic curricula were generated using templates with slight variations in personal data. The algorithm’s results were compared with evaluations made by a Human Resources collaborator and external paid recruitment platforms. The study’s findings indicate that CurEval effectively filters out irrelevant curricula, reducing the screening workload for HR professionals. The algorithm aligns with human evaluations, ensuring accurate classification of curricula according to vacancy requirements. Additionally, bias analysis revealed no evidence of discriminatory bias in the algorithm or human evaluations in the sample data. Further improvements for CurEval include expanding the list of keywords, incorporating natural language processing techniques, and integrating machine learning to enhance accuracy and adaptability. Real-time data integration, feedback loops with HR professionals, and integration with Applicant Tracking Systems are suggested to streamline the recruitment process. Multi-lingual support, performance metrics, and ongoing ethical considerations are also essential for refining and maintaining the algorithm’s effectiveness and fairness. CurEval offers promising potential to revolutionize the curricula evaluation process, enabling faster and more efficient screening while ensuring fairness and equal opportunity. Future work should focus on enhancing the algorithm’s capabilities, addressing biases, and continuously validating and improving its performance through collaboration and feedback from HR professionals.A automação da análise e classificação de currículos tem sido alvo de estudo e destaque nas últimas décadas, guiado pela evolução e aperfeiçoamento dos algoritmos de Inteligência Artificial e da Machine Learning. Nesta dissertação vai ser abordado o processo de análise e classificação destes assim como as questões éticas e bias associados ao processo que advém da natureza humana e das vivências individuais do recrutador. De forma a se evitar que estes ocorram durante o processo de recrutamento foi desenvolvido um algoritmo de análise e classificação dos currículos de acordo com a vaga em questão. Para além deste serão criados standards para a classificação e análise dos currículos, independentemente da sua origem e dos formatos. O algoritmo utiliza um conjunto pré-definido de palavras-chave e um formato de arquivo CSV para entrada, facilitando a estruturação e processamento dos dados. Para validar o desempenho do algoritmo e abordar preocupações de privacidade, currículos sintéticos foram gerados usando modelos com pequenas variações nos dados pessoais. Os resultados do algoritmo foram comparados com avaliações feitas por um colaborador de Recursos Humanos e plataformas externas de recrutamento pagas. Os resultados do estudo indicam que o CurEval filtra efetivamente currículos irrelevantes, reduzindo a carga de trabalho de triagem para os profissionais de RH. Este está alinhado com as avaliações humanas, garantindo a classificação precisa dos currículos de acordo com os requisitos das vagas. Além disso, a análise de viés discriminatórios revelou que não há evidências da existência dos mesmos no algoritmo ou nas avaliações humanas para a amostragem. Melhorias futuras para o CurEval incluem a expansão da lista de palavras-chave, a incorporação de técnicas de processamento de linguagem natural e a integração de Machine Learning para aprimorar a precisão e adaptabilidade. Integração de dados em tempo real, ciclos de feedback com profissionais de RH e integração com Sistemas de Acompanhamento de Candidatos são sugeridos para otimizar o processo de recrutamento. Suporte a múltiplos idiomas, métricas de desempenho e considerações éticas contínuas são essenciais para refinar e manter a eficácia e equidade do algoritmo

The Proposal of Effective System of Personal Marketing in Selected Company

Obsah této diplomové práce se zaměřuje na poměrně novou součást marketingu – personální marketing, jeho analýzu a následnou aplikaci ve společnosti ABB Česká republika, s.r.o. Personální marketing do jisté míry propojuje kvantitativní a kvantitativní metody marketingu s činnostmi a cíli personálního managementu. Záměrem této práce je aplikaci personálního managementu do jednotlivých fází marketingového procesu za účelem vytvoření teoretického rámce metod a technik potřebných k průzkumu současných aktivit personálního marketingu, stanovení nedostatků a jejich následné řešení.Content of the thesis is focused on relatively new part of marketing – Human Resource Marketing and its analysis and implementation to the ABB Czech Republic, s.r.o. HR marketing intertwines quantitative and quantitative methods of marketing together with activities and objectives of personnel management. Challenge of the thesis is application of personnel management into marketing process which would provide theoretical framework of methods and techniques to analyze present situation and help to determine and solve a problem related to the corporate personnel marketing system.