Knowledge and Information Systems

article

A statistical framework for mining substitution rules

Wei-Guang Teng, Ming-Jyh Hsieh, Ming-Syan Chen

Knowledge and Information Systems > 2005 > 7 > 2 > 158-178

In this paper, a new mining capability, called mining of substitution rules, is explored. A substitution refers to the choice made by a customer to replace the purchase of some items with that of others. The mining of substitution rules in a transaction database, the same as that of association rules, will lead to very valuable knowledge in various aspects, including market prediction, user behaviour...

article

Accelerating EM clustering to find high-quality solutions

Carlos Ordonez, Edward Omiecinski

Knowledge and Information Systems > 2005 > 7 > 2 > 135-157

Clustering is one of the most important techniques used in data mining. This article focuses on the EM clustering algorithm. Two fundamental aspects are studied: achieving faster convergence and finding higher quality clustering solutions. This work introduces several improvements to the EM clustering algorithm, being periodic M steps during initial iterations, reseeding of low-weight clusters and...

article

A quantitative analysis of the robustness of knowledge-based systems through degradation studies

Perry Groot, Annette ten Teije, Frank van Harmelen

Knowledge and Information Systems > 2005 > 7 > 2 > 224-245

The overall aim of this paper is to provide a general setting for quantitative quality measures of knowledge-based system behaviour that is widely applicable to many knowledge-based systems. We propose a general approach that we call degradation studies: an analysis of how system output changes as a function of degrading system input, such as incomplete or incorrect data or knowledge. To show the...

article

An evolutionary approach for automatically extracting intelligible classification rules

I. De Falco, A. Della Cioppa, A. Iazzetta, E. Tarantino

Knowledge and Information Systems > 2005 > 7 > 2 > 179-201

The process of automatically extracting novel, useful and ultimately comprehensible information from large databases, known as data mining, has become of great importance due to the ever-increasing amounts of data collected by large organizations. In particular, the emphasis is devoted to heuristic search methods able to discover patterns that are hard or impossible to detect using standard query...

article

Multiknowledge for decision making

QingXiang Wu, David Bell, Martin McGinnity

Knowledge and Information Systems > 2005 > 7 > 2 > 246-266

The representation of knowledge has an important effect on automated decision-making. In this paper, vector spaces are used to describe a condition space and a decision space, and knowledge is represented by a mapping from the condition space to the decision space. Many such mappings can be obtained from a training set. A set of mappings, which are created from multiple reducts in the training set,...

article

MotifMiner: Efficient discovery of common substructures in biochemical molecules

Matt Coatney, Srinivasan Parthasarathy

Knowledge and Information Systems > 2005 > 7 > 2 > 202-223

Biochemical research often involves examining structural relationships in molecules since scientists strongly believe in the causal relationship between structure and function. Traditionally, researchers have identified these patterns, or motifs, manually using domain expertise. However, with the massive influx of new biochemical data and the ability to gather data for very large molecules, there...

INFONA - science communication portal

Knowledge and Information Systems

A statistical framework for mining substitution rules

Accelerating EM clustering to find high-quality solutions

A quantitative analysis of the robustness of knowledge-based systems through degradation studies

An evolutionary approach for automatically extracting intelligible classification rules

Multiknowledge for decision making

MotifMiner: Efficient discovery of common substructures in biochemical molecules

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INFONA - science communication portal

Knowledge and Information Systems

A statistical framework for mining substitution rules

Accelerating EM clustering to find high-quality solutions

A quantitative analysis of the robustness of knowledge-based systems through degradation studies

An evolutionary approach for automatically extracting intelligible classification rules

Multiknowledge for decision making

MotifMiner: Efficient discovery of common substructures in biochemical molecules

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