xbrecs

XBRecs is an explainable book recommender system which bases its recommendations on book descriptions manipulated using NLP techniques.

https://github.com/mrrodero/xbrecs

Science Score: 26.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
  • Academic publication links
  • Academic email domains
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (1.6%) to scientific vocabulary

Keywords

books nlp recommender-system xai
Last synced: 6 months ago · JSON representation

Repository

XBRecs is an explainable book recommender system which bases its recommendations on book descriptions manipulated using NLP techniques.

Basic Info
  • Host: GitHub
  • Owner: mrrodero
  • License: bsd-3-clause
  • Language: Jupyter Notebook
  • Default Branch: main
  • Homepage:
  • Size: 122 MB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Topics
books nlp recommender-system xai
Created over 2 years ago · Last pushed about 1 year ago
Metadata Files
Readme License Citation

README.md

Gua de instalacin y uso del sistema recomendador XBRecs

Servidor web local

Para probar el sistema en local, debers solicitar acceso a la base de datos contactando con mrrodero

Una vez tengas acceso, debes seguir estos pasos:

  1. Accede a la carpeta xrecommender.
  2. Ejecuta, desde la terminal en que vayas a lanzar el servidor, export DEBUG=True.
  3. Ahora, lanza el sistema con el comando make runserver.
  4. Listo! Ya puedes empezar a utilizar el sistema, creando un perfil de usuario y aadiendo libros que hayas ledo. Podrs acceder a la recomendacin desde la vista principal de la web.

Servidor web online

Aunque se recomienda probar la web localmente, tambin puedes probar el sistema recomendador XBRecs accediendo a su versin desplegada en Render. Sin embargo, es posible que a la hora de generar una recomendacin, el servidor tarde demasiado o deje de funcionar. Esto se debe a la latencia con la base de datos remota de NeonTech.

Owner

  • Login: mrrodero
  • Kind: user

GitHub Events

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Last Year
  • Delete event: 4
  • Issue comment event: 1
  • Push event: 3
  • Pull request event: 8
  • Create event: 4