The increment of spatial-temporal data (STD) collected in many domain areas, including bioinformatics, engineering, medicine, environment, telecommunication, computer vision and many more has leads towards the emergent of information technology initiatives that facilitate the knowledge acquisition, organization and dissemination among research community. The initiatives include but not exhaust ...

Time series data is of interest to most science and engineering disciplines and analysis techniques have been developed for hundreds of years. There have, however, in recent years been new developments in data mining techniques, such as frequent pattern mining, which take a different perspective of data. Traditional techniques were not meant for such pattern-oriented approaches. There is, as a ...

The localisation of defects in computer programmes is essential in software engineering and is important in domain-specific data mining. Existing techniques which build on call-graph mining localise defects well, but do not scale for large software projects. This paper presents a hierarchical approach with good scalability characteristics. It makes use of novel call-graph representations, frequ...

This paper narrates the experience of a Canadian university in reorienting its mining curriculum towards the goal of producing engineers who are sensitive to context. The authors acknowledge industry’s historical association with environmental degradation and imperialism, but counter that mining is necessary to provide the materials of civil infrastructure, particularly that required to reduce ...

This paper discusses an industrial case study in which data mining has been applied to solve a quality engineering problem in electronics assembly. During the assembly process, solder balls occur underneath some components of printed circuit boards. The goal is to identify the cause of solder defects in a circuit board using a data mining approach. Statistical process control and design of expe...

In this paper, data mining is used to analyze the differentiation of mammalian Mesenchymal Stem Cells (MSCs). A database comprising the key parameters which, we believe, influence the destiny of mammalian MSCs has been constructed. This paper introduces Classification Association Rule Mining (CARM) as a data mining technique in the domain of tissue engineering and initiates a new promising rese...

Motivated by the need for unification of the domain of data mining and the demand for formalized representation of outcomes of data mining investigations, we address the task of constructing an ontology of data mining. In this paper we present an updated version of the OntoDM ontology, that is based on a recent proposal of a general framework for data mining and it is aligned with the ontology ...

In this report we present a technology assessment of a spectrum of mathematical methods and software techniques for data mining, i.e., for nding patterns and regularities in sets of data. After an introduction to the subject, the second part of the paper describes the essentials of a variety of methods for data mining through supervised and un-supervised learning. In the third part of the repor...

For improvement of data mining technology, the advantages and disadvantages on respective data mining methods should be discussed by comparison under the same condition. For this purpose, the Coronary Heart Disease database (CHD DB) was developed in 2004, and the data mining competition was held in the International Conference on Knowledge-Based Intelligent Information and Engineering Systems (...

This paper tackles problems encountered in mining of incomplete data for knowledge discovery of construction databases. As historical construction data are expensive to collect, any waste of incomplete data means not only loss of knowledge but also increase of costs for knowledge discovery of construction engineering. Unfortunately, incompleteness is commonplace in the existing construction dat...