# A Comprehensive Comparative Study of Word and Sentence Similarity Measures

Source: [A Comprehensive Comparative Study of Word and Sentence Similarity Measures](<https://www.sota2.com/research/paper/68fa62ce1e209131ce9fb2ff>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-25T20:26:18.516Z

Authors: Issa Atoum, Ahmed Otoom, Narayanan Kulathuramaiyer

Published: 2016-02-17T19:33:47.000Z

## Abstract

Sentence similarity is considered the basis of many natural language tasks such as information retrieval, question answering and text summarization. The semantic meaning between compared text fragments is based on the words semantic features and their relationships. This article reviews a set of word and sentence similarity measures and compares them on benchmark datasets. On the studied datasets, results showed that hybrid semantic measures perform better than both knowledge and corpus based measures.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/1610.04533>)

[PDF](<https://arxiv.org/pdf/1610.04533.pdf>)