EduPLEx_API
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Recommendation, reporting & analytics
Recommendation, reporting & analytics
  • Experiments report
    • Key concepts
    • Data sources
    • First demonstrator: ESCO ontologies and semantic matching
    • Software design
      • Endpoints Sbert_eduplex
      • Setup Sbert_eduplex
    • AI Applications
    • Conclusions
    • Recommendation
    • Bibliography
  • Recommendation Engine
  • Reporting and predictive analytics
  • LRS User Journey Visualizer
  • AI Tutor - RAG system
    • LLM-augmented Retrieval and Ranking for Course Recommendations
    • Retrieval of course candidates when searching via title.
    • Answer Generation Evaluation
    • Chunk Size and Retrieval Evaluation
    • Chunking Techniques – Splitters
    • Golden Case CLAPNQ
    • Comparative Retrieval Performance: Modules vs Golden Case
    • LLM-based Evaluator for Context Relevance
    • Retrieval Performance Indexing pdf vs xapi, and Keywords vs Questions
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  • Software license
  • Architecture overview
  • Base data processing pipeline
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  1. Experiments report

Software design

PreviousFirst demonstrator: ESCO ontologies and semantic matchingNextEndpoints Sbert_eduplex

Last updated 4 months ago

As a proof of concept, an automated system was implemented in the prototype to match learning opportunity descriptions and titles with the ESCO taxonomy. This system enhances the categorization process for content providers by leveraging AI tools, streamlining the experience and improving accuracy. The project demonstrated the practical benefits of integrating advanced NLP techniques into educational content management workflows.

Software license

The source code for the site is licensed under the , which you can find in the file.

Architecture overview

Base data processing pipeline

MIT license
LICENSE
System architecture overview
Text processing pipeline