Data mining is the process of extracting and finding patterns in massive data sets using methods at the intersection of machine learning, statistics and database systems. It is an interdisciplinary subfield of computer science and statistics whose overall goal is to extract information from a data set and transform it into a comprehensible structure for further use, forming the analysis step of the wider knowledge discovery in databases process; beyond the raw analysis it also involves database and data management, data pre-processing, model and inference considerations, interestingness metrics, complexity considerations, post-processing of discovered structures, visualization and online updating. This description is adapted from Wikipedia contributors under CC BY-SA 4.0; changes were made. https://creativecommons.org/licenses/by-sa/4.0/
Facts
Disputed
Origin YearThe term itself appeared around 1990 in the database community; the statistical and analytical methods it draws on trace back much further (Bayes' theorem, 18th century; regression analysis, 19th century). Core ConcernExtracting patterns from large data sets using methods from machine learning, statistics and database systems 1 Connections
Associated With
Bioinformatics, Fields Field-to-field association; both are standard neighbouring areas of computing
Data Science, Fields Field-to-field association; both are standard neighbouring areas of computing
Source Wikipedia: Data mining
Includes
Source Wikipedia: Apriori algorithm
Source Christos Faloutsos (Wikipedia)
Source DBSCAN (Wikipedia)
Source Wikipedia: Edith Cohen
Source Hierarchical clustering (Wikipedia)
Source Wikipedia: Jiawei Han
Source Panos Ipeirotis (Wikipedia)
Source Ramakrishnan Srikant (Wikipedia)
Source Wikipedia: Sequential pattern mining
Source Usama Fayyad (Wikipedia)
Sources
1. Wikipedia: Data mining
Wikimedia FoundationLead section, para 1
Data mining is the process of extracting and finding patterns in massive data sets involving methods at the intersection of machine learning, statistics, and database systems.
Etymology section
The term data mining appeared around 1990 in the database community, with generally positive connotations.
- In Group: Data Management and Mining, lead section
View the Source Christos Faloutsos (Wikipedia)
Includes: Christos Faloutsos, LeadQuote, Includes: Christos Faloutsos, Lead
His research interests include data mining for streams and networks, fractals, indexing for multimedia and bio-informatics data bases, and performance.
Wikipedia: Apriori algorithm
Includes: Apriori Algorithm, Lead sentenceQuote, Includes: Apriori Algorithm, Lead sentence
Apriori is an algorithm for frequent item set mining and association rule learning over relational databases.
Wikipedia: Edith Cohen
Usama Fayyad (Wikipedia)
Ramakrishnan Srikant (Wikipedia)
Wikipedia: Sequential pattern mining
Wikipedia: Jiawei Han
Wikimedia FoundationIncludes: Jiawei Han, Infobox field and known_for, lead paragraphView the Source DBSCAN (Wikipedia)
Includes: DBSCAN Algorithm, LeadQuote, Includes: DBSCAN Algorithm, Lead
Density-based spatial clustering of applications with noise (DBSCAN) is a data clustering algorithm proposed by Martin Ester, Hans-Peter Kriegel, Jörg Sander, and Xiaowei Xu in 1996.
Hierarchical clustering (Wikipedia)
Includes: Hierarchical Clustering Algorithm, LeadQuote, Includes: Hierarchical Clustering Algorithm, Lead
In data mining and statistics, hierarchical clustering (also called hierarchical cluster analysis or HCA) is a method of cluster analysis that seeks to build a hierarchy of clusters.
BIRCH (Wikipedia)
Includes: BIRCH Algorithm, LeadQuote, Includes: BIRCH Algorithm, Lead
BIRCH (balanced iterative reducing and clustering using hierarchies) is an unsupervised data mining algorithm used to perform hierarchical clustering over particularly large data-sets.
Panos Ipeirotis (Wikipedia)
Includes: Panos Ipeirotis, LeadQuote, Includes: Panos Ipeirotis, Lead
His research focuses on data mining, crowdsourcing, human computation, and the economics of online information systems.
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