---
title: "Using Information Content to Evaluate Semantic Similarity in a Taxonomy"
authors:
  - "Philip Resnik"
doi: ""
url: "https://ijcai.org/proceedings/1995/59"
pdf: "https://ijcai.org/proceedings/1995/0059.pdf"
venue: "Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence"
year: 1995
pages: "448-452"
track: "Cognitive Modelling"
keywords:
---

# Using Information Content to Evaluate Semantic Similarity in a Taxonomy

Philip Resnik

*Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence*, pages 448-452.

## Abstract

This paper presents a new measure of semantic similarity in an IS-A taxonomy, based on the notion of information content. Experimental evaluation suggests that the measure performs encouragingly well (a correlation of r = 0.79 with a benchmark set of human similarity judgments , with an upper bound of r = 0.90 for human subjects performing the same task), and significantly better than the traditional edge counting approach (r = 0.66) .