Sentence examples for mining and decision making from inspiring English sources
Despite the technological advances in bioinformatics computational methods, humans are an indispensable part of the data mining and decision making process.
The use of multimodal neuroimaging technologies has the advantages to overcome the limitations of any individual imaging modality and to aggregate clinical characteristics and features obtained from different imaging techniques for knowledge mining and for guiding medical diagnosis and decision making [2].
Data mining from existing County soil surveys can improve the utility of maps for research, management and decision making.
Data mining is a process that uses available technology to bridge the gap between data and logical decision making.
They develop and support software systems; they procure and make external scientific content available and actionable by scientists throughout the company; they implement and maintain workflow systems, such as e-lab notebooks, for both drug discovery and regulated functions; and they support and perform data, image, and text mining and analysis to support scientific decision making.
High-utility pattern mining (HUPM) is an emerging topic in recent years instead of association-rule mining to discover more interesting and useful information for decision making.
In real life, underground mining method selection is one of the multiple attribute decision making (MADM) problems and decision makers have always some difficulties in making the right decision in the multiple criteria environment.
Crucially, instead of basing major business decisions on intuition, they need to mine the data and information at their disposal to drive rapid decision making.
Based on information systems, data mining and Extension Theory (Extenics), we present a knowledge cultivating method and design a knowledge management platform for improve decision making quality.
The analysis combines the advantages of statistical approach (regression analysis) and data mining techniques (decision tree) for generation of easily interpretable rules for clinical decision making [ 12].
