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

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