2 citations · 2 across the 4 of their papers we have counts for
5 papers
When Occupation-derived Skills Don't Help: On the Limits of Skill-Augmented Career Path Prediction
Ege Süalp, Elena Senger, Toine Bogers +1
Skills are widely assumed to play a central role in career transitions, motivating their use in career path prediction (CPP) systems. In this work, we critically examine whether ex…
Term-Centric Hierarchy Induction from Heterogeneous Corpora
Elena Senger, Yuri Campbell, Jan-Peter Bergmann +2
Organizing knowledge from diverse text sources into interpretable hierarchies is crucial for tasks such as policy analysis, innovation monitoring, and exploratory domain mapping. E…
Crossing Domains without Labels: Distant Supervision for Term Extraction
Elena Senger, Yuri Campbell, Rob van der Goot +1
Automatic Term Extraction (ATE) is a critical component in downstream NLP tasks such as document tagging, ontology construction and patent analysis. Current state-of-the-art method…
KARRIEREWEGE: A Large Scale Career Path Prediction Dataset
Elena Senger, Yuri Campbell, Rob van der Goot +1
Accurate career path prediction can support many stakeholders, like job seekers, recruiters, HR, and project managers. However, publicly available data and tools for career path pr…
Deep Learning-based Computational Job Market Analysis: A Survey on Skill Extraction and Classification from Job Postings
Elena Senger, Mike Zhang, Rob van der Goot +1
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 th…