GT-Article-Recommendation | Scholarly Article Recommendation for Newbies

 by   payamsiyari JavaScript Version: Current License: MIT

kandi X-RAY | GT-Article-Recommendation Summary

kandi X-RAY | GT-Article-Recommendation Summary

GT-Article-Recommendation is a JavaScript library. GT-Article-Recommendation has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

Scholarly Article Recommendation for Newbies (GATech Course Project: CS6242, Spring 2016)
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            kandi-support Support

              GT-Article-Recommendation has a low active ecosystem.
              It has 0 star(s) with 0 fork(s). There are 1 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              GT-Article-Recommendation has no issues reported. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of GT-Article-Recommendation is current.

            kandi-Quality Quality

              GT-Article-Recommendation has no bugs reported.

            kandi-Security Security

              GT-Article-Recommendation has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

            kandi-License License

              GT-Article-Recommendation is licensed under the MIT License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              GT-Article-Recommendation releases are not available. You will need to build from source code and install.
              Installation instructions, examples and code snippets are available.

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            GT-Article-Recommendation Key Features

            No Key Features are available at this moment for GT-Article-Recommendation.

            GT-Article-Recommendation Examples and Code Snippets

            No Code Snippets are available at this moment for GT-Article-Recommendation.

            Community Discussions

            No Community Discussions are available at this moment for GT-Article-Recommendation.Refer to stack overflow page for discussions.

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

            Vulnerabilities

            No vulnerabilities reported

            Install GT-Article-Recommendation

            PREREQUISITES You will need the prerequisites below: SQLite >= 3.8.3 (E.g. the software does not work under Ubuntu 14.4 because it has SQLite 3.8.2 installed as built-in db and apparently it is difficult to upgrade it.) Django >= 1.9 (Installation link: https://www.djangoproject.com/download/) Database file scholar_sensemaking.db (access restricted to the instructor) This file needs to be placed in the following path: CSE6242ProjectRoot/graphists/ProjectApp Note: The file was provided by the course instructor and it is not publicly available. Hence, please do not share the database at any costs. NetworkX package (Install using pip install networkx)
            RUN To run the software: Change the directory to: CSE6242ProjectRoot/graphists Run: python manage.py collectstatic;python manage.py migrate;python manage.py runserver Open a web-browser and enter this url: http://127.0.0.1:8000 If for some reason the browser does not load or the software does not work, clear your browser cache files and try the above again.
            INFO Developed files are as follow (Also includes the libraries used):
            CONTACT Please contact payamsiyari@gmail.com if you encounter any issues.

            Support

            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
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            CLONE
          • HTTPS

            https://github.com/payamsiyari/GT-Article-Recommendation.git

          • CLI

            gh repo clone payamsiyari/GT-Article-Recommendation

          • sshUrl

            git@github.com:payamsiyari/GT-Article-Recommendation.git

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