Introduction
Keyword-based search has long been the default approach for reviewer discovery in STM publishing. It’s structured, familiar, and easy to control. But as research becomes more interdisciplinary and terminology evolves faster than ever, this approach is starting to show its limits.
The result is a hidden loss of reviewer coverage, often exceeding 30%, not because the expertise doesn’t exist, but because the system fails to recognize it.
Why do Boolean queries miss relevant reviewers?
Boolean queries operate on rigid logic. They match exact terms and combinations, but research language is rarely that consistent.
- The same concept can be described in multiple ways
- Emerging fields evolve terminology faster than indexing systems can adapt
- Researchers from adjacent domains may not use the same keywords at all
FAQs
What is the main limitation of Boolean search in STM?
Boolean search relies on exact keyword matches, which means it often misses relevant reviewers who use different terminology.
How much reviewer coverage is typically lost with keyword search?
Studies indicate that 30% or more relevant reviewers can be missed due to limitations in keyword-based matching.
Final thought
The issue isn’t that keyword search is broken. It’s that it’s incomplete. Concept extraction doesn’t just improve search. It changes what’s possible in reviewer discovery.
