The Taxonomy Matching App

The Taxonomy Matching Project is a specialized web application designed to streamline the process of mapping and standardizing subject taxonomies in educational content. It helps content managers and educators align various subject classifications with standardized taxonomies. This is an internal tool built to freelancers that are not comprehensive subject matter experts.

Key Features

  • Pre-processing in Python using the Sentence Transformer library for semantic similarity, clustering and paraphrase detection

  • Interactive subject-matching interface

  • Multiple match options (AI-suggested and manual matches)

  • Real-time search functionality across different taxonomy systems

  • Progress tracking for matching efforts

  • Preview system for comparing original and matched subjects

  • Export capability for matched results

Problems Solved

  1. Standardization Challenge: Helps organizations standardize their subject classifications across different content systems

  2. Efficiency: Reduces the manual effort required to map subjects by providing AI-suggested matches

  3. Accuracy: Enables users to review and verify matches with a detailed preview system

  4. Consistency: Ensures uniform taxonomy application across educational content

  5. Progress Tracking: Provides visibility into the matching progress and remaining work

Try The App: Taxonomy Matching Project

uid: demo@dekagrowth.io
pwd: demo

Technology Stack

  • Frontend:

    • React with TypeScript for robust component development

    • Vite for fast development and building

    • Tailwind CSS with shadcn-ui for modern, responsive styling

    • React Query for efficient data fetching and caching

  • Backend:

    • Supabase for:

      • User authentication

      • Database management (PostgreSQL)

      • Real-time data updates

      • Row-level security

  • Data Structure:

    • Supports multiple taxonomy systems:

      • Web Classification system

      • BISAC (Book Industry Standards and Communications)

      • Custom taxonomies