This is Part II of the two-part comprehensive survey devoted to a computing framework most
commonly known under the names Hyperdimensional Computing and Vector Symbolic …

Abstract Vector Symbolic Architectures combine a high-dimensional vector space with a set
of carefully designed operators in order to perform symbolic computations with large …

This article describes the use of continuous vector space models for reasoning with a formal
knowledge base. The practical significance of these models is that they support fast …

We propose a transformation of real input vectors to output binary vectors by projection
using a binary random matrix with elements {0, 1} and thresholding. We investigate the rate …

Analogy-making is a key function of human cognition. Therefore, the development of
computational models of analogy that automatically learn from examples can lead to …

Abstract Properties of randomized binary vector representations with adjustable sparseness
are investigated. Such representations are formed from input vectors by projecting them …

We analyze the estimation of the angle, scalar product, and the Euclidean distance of real-
valued vectors using binary vectors with controlled sparsity. Transformation is carried out by …

Users of a Web site usually perform their interest-oriented actions by clicking or visiting Web
pages, which are traced in access log files. Clustering Web user access patterns may …

This article proposes to use a binary random matrix with the elements {0, 1} to project input
floating-point vectors onto output floating-point vectors of smaller dimension. The accuracies …

In this paper we present a novel technique to capture Web users' behaviour based on their
interest-oriented actions. In our approach we utilise the vector space model Random …