mlsanityData to 14 Oct 2026

Measuring Sentences Similarity: A Survey

arXiv 1910.03940 ↗First posted 6 Oct 2019cs.CL cs.IRcited by 9

Not on the map. Why?

Abstract (arXiv)

This study is to review the approaches used for measuring sentences similarity. Measuring similarity between natural language sentences is a crucial task for many Natural Language Processing applications such as text classification, information retrieval, question answering, and plagiarism detection. This survey classifies approaches of calculating sentences similarity based on the adopted methodology into three categories. Word-to-word based, structure based, and vector-based are the most widely used approaches to find sentences similarity. Each approach measures relatedness between short texts based on a specific perspective. In addition, datasets that are mostly used as benchmarks for evaluating techniques in this field are introduced to provide a complete view on this issue. The approaches that combine more than one perspective give better results. Moreover, structure based similarity that measures similarity between sentences structures needs more investigation.

Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). First posted on arXiv 6 Oct 2019.

Builds on

No reference list yet.

Built on by

Cited by year

Citing papers per year: 2021: 2; 2022: 2; 2023: 0; 2024: 2; 2025: 3.

9 papers.