Data Discovery
نویسندگان
چکیده
منابع مشابه
Automatic Discovery of Technology Networks for Industrial-Scale R&D IT Projects via Data Mining
Industrial-Scale R&D IT Projects depend on many sub-technologies which need to be understood and have their risks analysed before the project can begin for their success. When planning such an industrial-scale project, the list of technologies and the associations of these technologies with each other is often complex and form a network. Discovery of this network of technologies is time consumi...
متن کاملThe False Discovery Rate in Simultaneous Fisher and Adjusted Permutation Hypothesis Testing on Microarray Data
Background and Objectives: In recent years, new technologies have led to produce a large amount of data and in the field of biology, microarray technology has also dramatically developed. Meanwhile, the Fisher test is used to compare the control group with two or more experimental groups and also to detect the differentially expressed genes. In this study, the false discovery rate was investiga...
متن کاملKnowledge discovery from data?
(KDD) field draws on findings from statistics, databases, and artificial intelligence to construct tools that let users gain insight from massive data sets. People in business, science, medicine, academia, and government collect such data sets, and several commercial packages now offer general-purpose KDD tools. An important KDD goal is to “turn data into knowledge.” For example, knowledge acqu...
متن کاملFaults Discovery Using Mined Data
Fault discovery in the complex systems consist of model based reasoning, fault tree analysis, rule based inference methods, and other approaches. Model based reasoning builds models for the systems either by mathematic formulations or by results of experiments. Fault Tree Analysis shows the possible causes of a system malfunction by enumerating the suspect components and their respective failur...
متن کاملPattern Discovery from Biological Data
Extracting useful information from structured and unstructured biological data is crucial in the health industry. Some examples include medical practitioner’s need to identify breast cancer patient in the early stage, estimate survival time of a heart disease patient, or recognize uncommon disease characteristics which suddenly appear. Currently there is an explosion in biological data availabl...
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ژورنال
عنوان ژورنال: Data Science Journal
سال: 2013
ISSN: 1683-1470
DOI: 10.2481/dsj.grdi-005