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Topological Map for Binary Data

Mustapha Lebbah, Fouad Badran, Sylvie Thiria

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Abstract

We propose a new algorithm using topological map on binarydata. The usual Euclidean distance is replaced by binary distancemeasures, which take into account possible asymmetries of binarydata. The method is illustrated on an example taken from literature.Finally an application from chemistry is presented. We show theeficiency of the proposed method when applied to high-dimensinalbinary data.

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What this paper is about

We propose a new algorithm using topological map on binarydata. The usual Euclidean distance is replaced by binary distancemeasures, which take into account possible asymmetries of binarydata. The method is illustrated on an example taken from literature.Finally an application from chemistry is presented. We show theeficiency of the proposed method when applied to high-dimensinalbinary data.

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OpenAlex reports 20 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

We propose a new algorithm using topological map on binarydata. The usual Euclidean distance is replaced by binary distancemeasures, which take into account possible asymmetries of binarydata. The method is illustrated on an example taken from literature.Finally an application from chemistry is presented. We show theeficiency of the proposed method when applied to high-dimensinalbinary data.

Key concepts: Binary number, Binary data, Euclidean distance, Computer science, Euclidean geometry, Random binary tree, Topology (electrical circuits), Algorithm

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