Publication Date: 2023/07/04
Abstract: Introduction – Human capital informatics is a computation technique to People management. Human Resource Planning has advanced tremendously during the last century. It evolved from a strategic to a fundamental strategy. It enables your firm to measure the impact of a selection of HR KPIs on organizational effectiveness and adopt data-driven judgments. Purpose – HR is expected to accomplish objectives, the function of HR is shifting from data collection to data interpretation. HR is, unfortunately, one of the most under-resourced areas in most companies. Machine Intelligence in HR Resource management helps businesses run effectively and successfully. HR departments can make smarter judgments, eliminate prejudices, and boost productivity in their businesses. So, the major goal here is to provide organizations with the best job seekers depending on their skill preferences and potential business places. Methodology – Using different matching techniques, we can achieve a proper set of candidates for firms that have some set of skills or subjects listed and the candidates are also experienced in those skills or subjects. Here we are trying to match skills of students with company required skills and then we are using different constraints with skills preference matching like location and Myers-Briggs Type Indicator (MBTI). Statistical techniques for matching like Multiple Preferences Matching Algorithm (MPMA) will be utilized for the matching process. Competing with the present statistical models we have employed other machine learning techniques like word-2-vec and latent semantic techniques. Findings – After performing Skill Preference Matching, we have concluded that MPMA is giving better results Now we are looking for other points to capture like match quality, global search, and controllability.
Keywords: Artificial Intelligence, Human Resource Analytics, Human Resource Management, Semantic Analysis, Statistical Models
DOI: https://doi.org/10.5281/zenodo.8208010
PDF: https://ijirst.demo4.arinfotech.co/assets/upload/files/IJISRT23JUN2166.pdf
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