C&SA | Contents

Volume 48>№ 1 JANUARY — FEBRUARY 2012

UDC 004.22 + 004.93’11

Rachkovskij D.A.,¹ Misuno I.S.,² Slipchenko S.V.³
¹International Scientific-Educational Center of Information Technologies and Systems, National Academy of Sciences and Ministry of Education and Science, Youth and Sports of Ukraine, Kyiv, Ukraine,
e-mail: dar@infrm.kiev.ua.
²International Scientific-Educational Center of Information Technologies and Systems, National Academy of Sciences and Ministry of Education and Science, Youth and Sports of Ukraine, Kyiv, Ukraine,
e-mail: i.misuno@gmail.com.
³International Scientific-Educational Center of Information Technologies and Systems, National Academy of Sciences and Ministry of Education and Science, Youth and Sports of Ukraine, Kyiv, Ukraine,
e-mail: serge.slipchenko.irtcits@gmail.com.

RANDOMIZED PROJECTIVE METHODS FOR CONSTRUCTION OF BINARY SPARSE VECTOR REPRESENTATIONS

// Kibernetika i sistemnyj analiz. 2012. Vol. 48, N 1. P. 175–187.

Abstract. We investigate the properties of randomized binary vector representations with adjustable sparseness formed from the input vectors by projecting them using a random matrix with ternary elements {–1, 0, +1}. We analyze the accuracy of estimating the measures of similarity-difference of the source vectors having a floating-point format by the output binary vectors. Those vector representations can be used for an efficient processing of large volumes of input multidimensional vectors in applications related to search, classification, associative memory, etc. Figs: 6. Refs: 25 titles.

Keywords: random projection, vector representation, sparse binary representation, distributed representation, efficient similarity estimation.

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