# Semantic Technology-Assisted Review (STAR) Document analysis and monitoring using random vectors

arXiv: https://arxiv.org/abs/1711.10307 · HTML: https://mlsanity.com/paper/1711.10307/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 Nov 2017.

## Built on by (most cited first, 1 of 1)

- [A Training-Free, Alignment-Free Approach to Corporate Intelligence: Application to SEC Filings](https://mlsanity.com/paper/2609.11620/) (2026)

## Abstract (arXiv)

The review and analysis of large collections of documents and the periodic monitoring of new additions thereto has greatly benefited from new developments in computer software. This paper demonstrates how using random vectors to construct a low-dimensional Euclidean space embedding words and documents enables fast and accurate computation of semantic similarities between them. With this technique of Semantic Technology-Assisted Review (STAR), documents can be selected, compared, classified, summarized and evaluated very quickly with minimal expert involvement and high-quality results.