Scholar Mesh is a scientific reviewer discovery service built on large-scale scholarly metadata, including more than 4 million authors and 8 million publications in computer science, machine learning, and related fields.
Why this service exists
Peer review quality depends on finding independent domain experts. As publication volume continues to grow, reviewer discovery has become slower and more error-prone for authors, conference organizers, and editors. Scholar Mesh is designed to make this search process faster and more transparent.
Research output keeps increasing, so reviewer discovery must scale with it.
How Scholar Mesh works
- Users provide article metadata: authors, title, area, and abstract.
- The recommender system retrieves and ranks expert candidates.
- Conflict filters remove direct co-authors and same-organization candidates where possible.
Who it helps
- Scientists looking for reviewer suggestions for manuscripts.
- Conference organizers building Programme Committees.
- Journal editors identifying reviewers and editorial board candidates.
More updates
Product and methodology updates are published on the Scholar Mesh blog.