Tree Edit Distance (TED)

Catalogue of Tools & Metrics for Trustworthy AI

These tools and metrics are designed to help AI actors develop and use trustworthy AI systems and applications that respect human rights and are fair, transparent, explainable, robust, secure and safe.

Overview Tools Metrics About the catalogue

Website

Tree Edit Distance (TED) is a metric for calculation of similarity between syntactic n-grams for further detection of soft similarity between texts.

About the metric

You can click on the links to see the associated metrics

Objective(s):

Robustness & digital security
Transparency & explainability

Purpose(s):

Event/anomaly detection
Recognition/object detection

Lifecycle stage(s):

Build & interpret model
Plan & design

Target users:

Developer
Project manager

Risk management stage(s):

Define
Assess

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Disclaimer: The tools and metrics featured herein are solely those of the originating authors and are not vetted or endorsed by the OECD or its member countries. The Organisation cannot be held responsible for possible issues resulting from the posting of links to third parties' tools and metrics on this catalogue. More on the methodology can be found at https://oecd.ai/catalogue/faq.