16 Facts About Information mining

Data Information mining is the process of extracting and discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems.

Data mining is an interdisciplinary subfield of computer science and statistics with an overall goal of extracting information from a data set and transforming the information into a comprehensible structure for further use.

Data Information mining is the analysis step of the "knowledge discovery in databases" process, or KDD.

Term "data Information mining" is a misnomer because the goal is the extraction of patterns and knowledge from large amounts of data, not the extraction of data itself.

Actual data Information mining task is the semi-automatic or automatic analysis of large quantities of data to extract previously unknown, interesting patterns such as groups of data records, unusual records, and dependencies .

Related searches

In contrast, data Information mining uses machine learning and statistical models to uncover clandestine or hidden patterns in a large volume of data.

The term "data Information mining" was used in a similarly critical way by economist Michael Lovell in an article published in the Review of Economic Studies in 1983.

Term data Information mining appeared around 1990 in the database community, with generally positive connotations.

However, the term data Information mining became more popular in the business and press communities.

Data Information mining is the process of applying these methods with the intention of uncovering hidden patterns.

For example, a data Information mining algorithm trying to distinguish "spam" from "legitimate" e-mails would be trained on a training set of sample e-mails.

Data Information mining is used wherever there is digital data available today.

Notable examples of data Information mining can be found throughout business, medicine, science, and surveillance.

Ways in which data Information mining can be used can in some cases and contexts raise questions regarding privacy, legality, and ethics.

Data mining requires data preparation which uncovers information or patterns which compromise confidentiality and privacy obligations.

Since 2020 Switzerland has been regulating data Information mining by allowing it in the research field under certain conditions laid down by art.