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Data 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. [1] Data mining is an interdisciplinary subfield of computer science and statistics with an overall goal of extracting information (with intelligent methods) from a ...
In business, data mining is the analysis of historical business activities, stored as static data in data warehouse databases. The goal is to reveal hidden patterns and trends. Data mining software uses advanced pattern recognition algorithms to sift through large amounts of data to assist in discovering previously unknown strategic business ...
Relational data mining is the data mining technique for relational databases. [1] Unlike traditional data mining algorithms, which look for patterns in a single table (propositional patterns), relational data mining algorithms look for patterns among multiple tables (relational patterns). For most types of propositional patterns, there are ...
Rakesh has been granted more than 55 patents. He has published more than 150 research papers, many of them considered seminal. He has written the 1st as well as 2nd highest cited of all papers in the fields of databases and data mining (13th and 15th most cited across all computer science as of February 2007 in CiteSeer).
Oracle Data Mining (ODM) is an option of Oracle Database Enterprise Edition. It contains several data mining and data analysis algorithms for classification , prediction , regression , associations , feature selection , anomaly detection , feature extraction , and specialized analytics.
Data mining is a particular data analysis technique that focuses on statistical modeling and knowledge discovery for predictive rather than purely descriptive purposes, while business intelligence covers data analysis that relies heavily on aggregation, focusing mainly on business information. [4]
Text mining, text data mining (TDM) or text analytics is the process of deriving high-quality information from text. It involves "the discovery by computer of new, previously unknown information, by automatically extracting information from different written resources." [1] Written resources may include websites, books, emails, reviews, and ...
The term OLAP was created as a slight modification of the traditional database term online transaction processing (OLTP). [2] OLAP is part of the broader category of business intelligence, which also encompasses relational databases, report writing and data mining. [3]