3 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.CL2026
Building a Custom Taxonomy of AI Skills and Tasks from the Ground Up with Job Postings
Stephen Meisenbacher, Peter Norlander
Utilizing LLMs for automated taxonomy construction presents a clear opportunity for the comprehensive, yet efficient mapping of potentially complex domains. When contending with hi…
cs.CY2025
Extracting O*NET Features from the NLx Corpus to Build Public Use Aggregate Labor Market Data
Stephen Meisenbacher, Svetlozar Nestorov, Peter Norlander
Data from online job postings are difficult to access and are not built in a standard or transparent manner. Data included in the standard taxonomy and occupational information dat…
cs.CL2023★ 3 cited
Transforming Unstructured Text into Data with Context Rule Assisted Machine Learning (CRAML)
Stephen Meisenbacher, Peter Norlander
We describe a method and new no-code software tools enabling domain experts to build custom structured, labeled datasets from the unstructured text of documents and build niche mac…