A Single-Pass Triclustering Algorithm

被引：4

作者：

Gnatyshak, D. V. ^{[1
]}

机构：

[1] Natl Res Univ, Higher Sch Econ, Sci & Educ Lab Intelligent Syst & Struct Anal, Moscow, Russia

来源：

AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS | 2015年 / 49卷 / 01期

关键词：

formal concept analysis; data analysis; clustering; triclustering; big data; linear algorithm; single-pass algorithm;

D O I：

10.3103/S0005105515010057

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

As the popularity of the field of big data continues to rise, the problem of the development of efficient algorithms with low time complexity and that ability to be parallelized is more and more frequently posed. This work is aimed at the development of an efficient single-pass algorithm for the triclustering of binary data that is suitable for use in the field of big data. As a result, a single-pass serial online OAC triclustering algorithm (triclustering of object-attribute-condition) was obtained. This algorithm not only has a very low complexity in time and memory, but it also can be effectively parallelized.

引用

页码：27 / 41

页数：15

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