Hierarchical heuristics for Boolean-reasoning-based binary bicluster induction

IF 0.4 4区计算机科学 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS

Acta Informatica Pub Date : 2022-01-21 DOI:10.1007/s00236-021-00415-9

Marcin Michalak

引用次数: 2

Abstract

Biclustering is a two-dimensional data analysis technique that, applied to a matrix, searches for a subset of rows and columns that intersect to produce a submatrix with given, expected features. Such an approach requires different methods to those of typical classification or regression tasks. In recent years it has become possible to express biclustering goals in the form of Boolean reasoning. This paper presents a new, heuristic approach to bicluster induction in binary data.

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基于布尔推理的二元双聚类归纳的层次启发式方法

双聚类是一种二维数据分析技术，它应用于矩阵，搜索相交的行和列的子集，以产生具有给定预期特征的子矩阵。这种方法需要不同于典型分类或回归任务的方法。近年来，用布尔推理的形式来表达双聚类目标已经成为可能。本文提出了一种新的、启发式的二值数据双聚类归纳方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Acta Informatica 工程技术-计算机：信息系统

CiteScore

2.40

自引率

16.70%

发文量

审稿时长

>12 weeks

期刊介绍： Acta Informatica provides international dissemination of articles on formal methods for the design and analysis of programs, computing systems and information structures, as well as related fields of Theoretical Computer Science such as Automata Theory, Logic in Computer Science, and Algorithmics. Topics of interest include: • semantics of programming languages • models and modeling languages for concurrent, distributed, reactive and mobile systems • models and modeling languages for timed, hybrid and probabilistic systems • specification, program analysis and verification • model checking and theorem proving • modal, temporal, first- and higher-order logics, and their variants • constraint logic, SAT/SMT-solving techniques • theoretical aspects of databases, semi-structured data and finite model theory • theoretical aspects of artificial intelligence, knowledge representation, description logic • automata theory, formal languages, term and graph rewriting • game-based models, synthesis • type theory, typed calculi • algebraic, coalgebraic and categorical methods • formal aspects of performance, dependability and reliability analysis • foundations of information and network security • parallel, distributed and randomized algorithms • design and analysis of algorithms • foundations of network and communication protocols.