L1 norm based multiplication-free cosine similarity measures for big data analysis

Date

2014-11

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International Workshop on Computational Intelligence for Multimedia Understanding, IWCIM 2014

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IEEE

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1 - 5

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English

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Abstract

The cosine similarity measure is widely used in big data analysis to compare vectors. In this article a new set of vector similarity measures are proposed. New vector similarity measures are based on a multiplication-free operator which requires only additions and sign operations. A vector 'product' using the multiplication-free operator is also defined. The new vector product induces the ℓ1-norm. As a result, new cosine measure-like similarity measures are normalized by the ℓ1-norms of the vectors. They can be computed using the MapReduce framework. Simulation examples are presented. © 2014 IEEE.

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