相关论文: Job Posting-Enriched Knowledge Graph for Skills-ba…

To cope with the accelerating pace of technological changes, talents are urged to add and refresh their skills for staying in active and gainful employment. This raises a natural question: what are the right skills to learn? Indeed, it is a…

Rapid technological innovation threatens to leave much of the global workforce behind. Today's economy juxtaposes white-hot demand for skilled labor against stagnant employment prospects for workers unprepared to participate in a digital…

We use algorithmic and network-based tools to build and analyze the bipartite network connecting jobs with the skills they require. We quantify and represent the relatedness between jobs and skills by using statistically validated networks.…

Resource allocation in business process management involves assigning resources to open tasks while considering factors such as individual roles, aptitudes, case-specific characteristics, and regulatory constraints. Current information…

This paper develops a new data-driven approach to characterizing latent worker skill and job task heterogeneity by applying an empirical tool from network theory to large-scale Brazilian administrative data on worker--job matching. We…

The fast adoption of new technologies forces companies to continuously adapt their operations making it harder to predict workforce requirements. Several recent studies have attempted to predict the emergence of new roles and skills in the…

Recent approaches in skill matching, employing synthetic training data for classification or similarity model training, have shown promising results, reducing the need for time-consuming and expensive annotations. However, previous…

Knowledge-intensive tasks pose a significant challenge for Machine Learning (ML) techniques. Commonly adopted methods, such as Large Language Models (LLMs), often exhibit limitations when applied to such tasks. Nevertheless, there have been…

Knowledge Graphs (KGs) have been used to support a wide range of applications, from web search to personal assistant. In this paper, we describe three generations of knowledge graphs: entity-based KGs, which have been supporting general…

Knowledge Graphs (KGs) are widely employed in artificial intelligence applications, such as question-answering and recommendation systems. However, KGs are frequently found to be incomplete. While much of the existing literature focuses on…

The rapid advancement of Generative AI (Gen AI) technologies, particularly tools like ChatGPT, is significantly impacting the labor market by reshaping job roles and skill requirements. This study examines the demand for ChatGPT-related…

With the widespread use of knowledge graphs (KG) in various automated AI systems and applications, it is very important to ensure that information retrieval algorithms leveraging them are free from societal biases. Previous works have…

Knowledge Graphs (KGs) represent real-world noisy raw information in a structured form, capturing relationships between entities. However, for dynamic real-world applications such as social networks, recommender systems, computational…

In a rapidly evolving job market, skill demand forecasting is crucial as it enables policymakers and businesses to anticipate and adapt to changes, ensuring that workforce skills align with market needs, thereby enhancing productivity and…

Feature selection in Knowledge Graphs (KGs) are increasingly utilized in diverse domains, including biomedical research, Natural Language Processing (NLP), and personalized recommendation systems. This paper delves into the methodologies…

In recent years, we have witnessed the proliferation of knowledge graphs (KG) in various domains, aiming to support applications like question answering, recommendations, etc. A frequent task when integrating knowledge from different KGs is…

Modern economies require increasingly diverse and specialized skills, many of which depend on the acquisition of other skills first. Here we analyse US survey data to reveal a nested structure within skill portfolios, where the direction of…

Despite the recent popularity of knowledge graph (KG) related tasks and benchmarks such as KG embeddings, link prediction, entity alignment and evaluation of the reasoning abilities of pretrained language models as KGs, the structure and…

Recent years have brought significant advances to Natural Language Processing (NLP), which enabled fast progress in the field of computational job market analysis. Core tasks in this application domain are skill extraction and…

The recruitment process is a slow and inefficient one at best, and a potentially ineffective one at worst. Matching candidates to jobs is one thing, but matching candidates with jobs alongside appropriate expectations and taking into…