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Reviewer Recommender

Reviewer Recommender
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Reviewer Recommender
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Introduction

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.

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

    -

  • Country Rank

    -

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%
More Data

Related Websites

Stability Matrix CivitAI Integration 

This document outlines the integration of Stability Matrix into Civitai. 

What is Stability Matrix?

Stability Matrix is a powerful tool for evaluating and comparing different AI models. It provides a comprehensive set of metrics to assess model performance across various tasks, including text generation, image generation, and code generation.

Benefits of Integrating Stability Matrix into Civitai:

* Enhanced Model Discovery: Users can easily identify high-performing models based on their desired tasks and preferences.
* Improved Model Selection: The detailed metrics provided by Stability Matrix allow for informed decision-making when choosing a model for a specific project.
* Community-Driven Evaluation: By leveraging the collective wisdom of the Civitai community, Stability Matrix fosters a transparent and collaborative approach to model evaluation.
* Accelerated Model Development: Developers can use Stability Matrix to track the progress of their models and identify areas for improvement.

Implementation Details:

* Stability Matrix scores will be displayed alongside model descriptions on Civitai.
* Users will be able to filter models based on their Stability Matrix scores.
* The integration will initially focus on text generation and image generation models.

Future Enhancements:

* Expand support for additional model types, such as code generation models.
* Implement interactive visualizations of Stability Matrix data.
* Allow users to contribute their own model evaluations to the platform.
View Detail

Stability Matrix CivitAI Integration This document outlines the integration of Stability Matrix into Civitai. What is Stability Matrix? Stability Matrix is a powerful tool for evaluating and comparing different AI models. It provides a comprehensive set of metrics to assess model performance across various tasks, including text generation, image generation, and code generation. Benefits of Integrating Stability Matrix into Civitai: * Enhanced Model Discovery: Users can easily identify high-performing models based on their desired tasks and preferences. * Improved Model Selection: The detailed metrics provided by Stability Matrix allow for informed decision-making when choosing a model for a specific project. * Community-Driven Evaluation: By leveraging the collective wisdom of the Civitai community, Stability Matrix fosters a transparent and collaborative approach to model evaluation. * Accelerated Model Development: Developers can use Stability Matrix to track the progress of their models and identify areas for improvement. Implementation Details: * Stability Matrix scores will be displayed alongside model descriptions on Civitai. * Users will be able to filter models based on their Stability Matrix scores. * The integration will initially focus on text generation and image generation models. Future Enhancements: * Expand support for additional model types, such as code generation models. * Implement interactive visualizations of Stability Matrix data. * Allow users to contribute their own model evaluations to the platform.

Stability Matrix CivitAI Integration This document outlines the integration of Stability Matrix into Civitai. What is Stability Matrix? Stability Matrix is a powerful tool for evaluating and comparing different AI models. It provides a comprehensive set of metrics to assess model performance across various tasks, including text generation, image generation, and code generation. Benefits of Integrating Stability Matrix into Civitai: * Enhanced Model Discovery: Users can easily identify high-performing models based on their desired tasks and preferences. * Improved Model Selection: The detailed metrics provided by Stability Matrix allow for informed decision-making when choosing a model for a specific project. * Community-Driven Evaluation: By leveraging the collective wisdom of the Civitai community, Stability Matrix fosters a transparent and collaborative approach to model evaluation. * Accelerated Model Development: Developers can use Stability Matrix to track the progress of their models and identify areas for improvement. Implementation Details: * Stability Matrix scores will be displayed alongside model descriptions on Civitai. * Users will be able to filter models based on their Stability Matrix scores. * The integration will initially focus on text generation and image generation models. Future Enhancements: * Expand support for additional model types, such as code generation models. * Implement interactive visualizations of Stability Matrix data. * Allow users to contribute their own model evaluations to the platform.

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Sketch2Code GPT4-128K GPT4-Vision - Sidebar 

This is a simple sidebar for a Sketch2Code application powered by GPT4-128K and GPT4-Vision. 

It likely contains:

* Upload Sketch: A button or area to upload an image sketch.
* Code Generation Options:  Settings to choose the programming language, desired code complexity, or other generation parameters.
* Output Code: A display area to show the generated code.
* Clear Output: A button to clear the generated code.


Let me know if you'd like me to elaborate on any specific aspect of the sidebar!
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Sketch2Code GPT4-128K GPT4-Vision - Sidebar This is a simple sidebar for a Sketch2Code application powered by GPT4-128K and GPT4-Vision. It likely contains: * Upload Sketch: A button or area to upload an image sketch. * Code Generation Options: Settings to choose the programming language, desired code complexity, or other generation parameters. * Output Code: A display area to show the generated code. * Clear Output: A button to clear the generated code. Let me know if you'd like me to elaborate on any specific aspect of the sidebar!

Sketch2Code GPT4-128K GPT4-Vision - Sidebar This is a simple sidebar for a Sketch2Code application powered by GPT4-128K and GPT4-Vision. It likely contains: * Upload Sketch: A button or area to upload an image sketch. * Code Generation Options: Settings to choose the programming language, desired code complexity, or other generation parameters. * Output Code: A display area to show the generated code. * Clear Output: A button to clear the generated code. Let me know if you'd like me to elaborate on any specific aspect of the sidebar!

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