Reviewer Recommender is a Chrome Extension developed by the Knowledge Engineering Group (KEG) at Tsinghua University. It integrates with the ScholarOne Reviewer System to automate the process of recommending reviewers for research papers. By leveraging academic big data from Aminer, this tool streamlines the reviewer selection process for journal editors and academic institutions.
Reviewer Recommender
Reviewer Recommender
Introduction
Feature
Automatic Paper Information Extraction
The extension seamlessly extracts paper information, including author details, directly from the ScholarOne Reviewer System. This feature eliminates manual data entry and reduces the potential for errors.
Intelligent Reviewer Recommendation
Utilizing Aminer's extensive academic database, Reviewer Recommender suggests the most appropriate reviewers for each paper. This data-driven approach ensures a more efficient and accurate reviewer selection process.
ScholarOne Integration
Designed specifically for the ScholarOne Reviewer System, this extension seamlessly integrates into existing workflows, enhancing productivity without disrupting established processes.
User-Friendly Interface
As a Chrome Extension, Reviewer Recommender offers a simple and intuitive user experience. It can be easily installed from the Chrome Web Store and used immediately with minimal setup.
Cost-Effective Solution
Reviewer Recommender is available as a free extension, making it an accessible tool for academic institutions and journal editors of all sizes.
FAQ
Is Reviewer Recommender a paid extension?
No, Reviewer Recommender is completely free to use. There are no subscription fees or hidden costs associated with the extension.
How does Reviewer Recommender work?
Reviewer Recommender utilizes academic big data from Aminer to analyze paper information and recommend suitable reviewers. It automatically extracts paper details from ScholarOne and uses this information to suggest the most appropriate reviewers based on their expertise and research areas.
Can I use Reviewer Recommender with other reviewer systems?
No, Reviewer Recommender is specifically designed to work with the ScholarOne Reviewer System. It is not compatible with other reviewer systems at this time.
Latest Traffic Insights
Monthly Visits
290.25 M
Bounce Rate
55.49%
Pages Per Visit
2.84
Time on Site(s)
113.64
Global Rank
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Country Rank
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Recent Visits
Traffic Sources
- Social Media:0.68%
- Paid Referrals:0.54%
- Email:0.11%
- Referrals:14.58%
- Search Engines:15.20%
- Direct:68.89%
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