Determining Tanimoto similarity neighborhoods of real-valued vectors by means of the triangle inequality and bounds on lengths

DOI10.1007/978-3-030-87334-9_2zbMath1495.68194OpenAlexW3201382079MaRDI QIDQ2670886

Marzena Kryszkiewicz

Publication date: 1 June 2022

Full work available at URL: https://doi.org/10.1007/978-3-030-87334-9_2

zbMATH Keywords

triangle inequalityneighborhoodnearest neighborsEuclidean distancecosine similaritybinary vectornear duplicatesreal-valued vectorTanimoto similarityvector length bounds

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Pattern recognition, speech recognition (68T10)

Cites Work

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• Satisfying general proximity/similarity queries with metric trees
• A proof of the triangle inequality for the Tanimoto distance
• Similarity search. The metric space approach.
• Using Non-Zero Dimensions for the Cosine and Tanimoto Similarity Search Among Real Valued Vectors
• Determining Cosine Similarity Neighborhoods by Means of the Euclidean Distance

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