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Topic: Data mining

Related Topics

Data warehouse

Relational data mining

Data Mining For Very Busy People

Data stream mining

Data warehousing

Data mart

Text mining

A priori algorithm

Business intelligence

Database management system

Abstraction (computer science)

OLAP

Star schema

Information technology

Coal mining

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	Data Mining Software, Data Mining Applications and Data Mining Solutions
		Data mining tools provide a number of techniques that can be applied to any business problem.
		Data mining tools are used to ensure flexibility and the greatest accuracy possible.
		Because data mining tools are so flexible, a set of data mining guidelines and a data mining methodology have been developed to help guide the process.
	www.spss.com /data_mining (592 words)

	Data mining - Wikipedia, the free encyclopedia
		Although the term "data mining" is usually used in relation to analysis of data, like artificial intelligence, it is an umbrella term with varied meanings in a wide range of contexts.
		Unlike data analysis, data mining is not based or focused on an existing model which is to be tested or whose parameters are to be optimized.
		Used in the technical context of data warehousing and analysis, the term "data mining" is neutral.
	en.wikipedia.org /wiki/Data_mining (2002 words)

	[No title] (Site not responding. Last check: )
		Data mining is the practice of automatically searching large stores of data for patterns.
		Data mining has been defined as "The nontrivial extraction of implicit, previously unknown, and potentially useful information from data" [1] and "The science of extracting useful information from large data sets or databases" [2].
		In spite of this, some exploratory data work is always required in any applied statistical analysis to get a feel for the data, so sometimes the line between good statistical practice and data mining is less than clear.
	wikiwhat.com /encyclopedia/d/da/data_mining.html (568 words)

	An Introduction to Data Mining
		Data mining, the extraction of hidden predictive information from large databases, is a powerful new technology with great potential to help companies focus on the most important information in their data warehouses.
		Data mining techniques can be implemented rapidly on existing software and hardware platforms to enhance the value of existing information resources, and can be integrated with new products and systems as they are brought on-line.
		Data mining techniques can yield the benefits of automation on existing software and hardware platforms, and can be implemented on new systems as existing platforms are upgraded and new products developed.
	www.thearling.com /text/dmwhite/dmwhite.htm (3639 words)

	Two Crows: Data mining glossary
		The maximum likelihood estimate of a parameter is the value of a parameter that maximizes the probability that the data came from the population defined by the parameter.
		Data not collected by the organization, such as data from a proprietary database, that is combined with the organization's own data.
		A collection of numeric data is standardized by subtracting a measure of central location (such as the mean or median) and by dividing by some measure of spread (such as the standard deviation, interquartile range or range).
	www.twocrows.com /glossary.htm (3689 words)

	Investor Home - Data Mining
		Data mining involves searching through databases for correlations and patterns that differ from results that would be anticipated to occur by chance or in random conditions.
		The practice of data mining in and of itself is neither good nor bad and the use of data mining has become common in many industries.
		The Professors reason that data mining can be detected by the complexity of the trading rule, the lack of a coherent story or theory, the performance of out-of-sample tests, and the adjustment of returns for risk, transaction costs, and taxes.
	www.investorhome.com /mining.htm (2507 words)

	Data Mining Techniques
		The process of data mining consists of three stages: (1) the initial exploration, (2) model building or pattern identification with validation/verification, and (3) deployment (i.e., the application of the model to new data in order to generate predictions).
		One of the preliminary stage in predictive data mining, when the data set includes more variables than could be included (or would be efficient to include) in the actual model building phase (or even in initial exploratory operations), is to select predictors from a large list of candidates.
		Data reduction is another possible objective for data mining (e.g., to aggregate or amalgamate the information in very large data sets into useful and manageable chunks).
	www.statsoft.com /textbook/stdatmin.html (4347 words)

	Data Mining Software, Data Mining Applications and Data Mining Solutions
		Both data mining tools and data mining applications are valuable, however.
		Increasingly, organizations are using data mining tools and data mining applications together in an integrated environment for predictive analytics.
		These two data mining technologies open a rich vein of customer data in the form of textual comments from survey research and log files from Web servers, which were previously unusable.
	www.spss.com /data_mining/index.htm?source=homepage&hpzone=tech (592 words)

	St@tServ - About Data Mining
		« Data mining is the process of discovering meaningful new correlations, patterns and trends by sifting through large amounts of data stored in repositories, using pattern recognition technologies as well as statistical and mathematical techniques.
		« Data mining is the exploration and analysis, by automatic and semiautomatic means, of large quantities of data in order to discover meaningful patterns and rules » (M.J.A. Berry, G. Linoff).
		« Data mining the use of advanced statistical tools to reach into a company’s existing databases to discover patterns and relationships that can be exploited in a business context» (Trajecta lexicon).
	www.statserv.com /datamining.html (538 words)

	What is data mining? - a definition from Whatis.com - see also: data miner, data analysis
		Data mining techniques are used in a many research areas, including mathematics, cybernetics, and genetics.
		Web mining, a type of data mining used in customer relationship management (CRM), takes advantage of the huge amount of information gathered by a Web site to look for patterns in user behavior.
		A data miner is a program that collects such information, often without the user's knowledge, as spyware.
	searchcrm.techtarget.com /sDefinition/0,,sid11_gci211901,00.html (258 words)

	Data Mining and Discovery
		Data mining is an AI powered tool that can discover useful information within a database that can then be used to improve actions.
		Using data mining to look at repayment trends, these enterprises have a good idea on who is going to default on a loan, for example.
		First applied in banking, data mining uses a variety of algorithms to sift through storehouses of data in search of 'noisy' patterns and relationships among the different silos of information.
	www.aaai.org /AITopics/html/mining.html (3275 words)

	Data mining [OCLC - Projects]
		If libraries are to realize the full value of their bibliographic data—or, put another way, if libraries are to maximize the return on the investments they make to create this data—steps must be taken to release this value in innovative and useful ways.
		However, this data needs to be made to work harder in order to create value for librarians and users.
		Currently available data include holdings and titles, each by place of publication (from OCLC WorldCat) and number of libraries, librarians, users, volumes, and annual expenditures (from other sources).
	www.oclc.org /research/projects/mining (625 words)

	Data Mining: Text Mining, Visualization and Social Media
		I like this in part because the data is presented in a manner that reflects the metaphor of the text (shadow).
		Note that according to the attention data comparing Obama and Clinton, the cross over point (the point at which relative attention flipped from favouring Clinton to favouring Obama) was around Jan 26.
		Polling data (reported by the BBC) shows the flip in the polls to be sometime in the Feb-March area.
	datamining.typepad.com /data_mining (941 words)

	Amazon.com: Data Mining: Books: Pieter Adriaans,Dolf Zantinge (Site not responding. Last check: )
		The whole data mining process, including data selection, cleaning, coding, different pattern recognition techniques and reporting, is illustrated by means of an extensive case study and numerous answers.
		This might be a good book for someone who is either contemplating a career move into this area, or for someone who is professionally affected by data mining and wants a "quick and dirty" as to what data mining can do and what it can't.
		However, it is one of the first in data mining and therefore the authors should be given some credit.
	www.amazon.com /Data-Mining-Pieter-Adriaans/dp/0201403803 (1022 words)

	Oracle Data Mining
		Oracle Data Miner is a graphical user interface for Oracle Data Mining that helps data analysts mine their Oracle data to find valuable hidden information, patterns, and new insights.
		With Oracle Data Miner and Oracle Data Mining, the data never leaves the database: all data movement is eliminated.
		META Group cited the maturity and stability of Oracle Data Mining and its widespread adoption relative to the competition.
	www.oracle.com /technology/products/bi/odm/index.html (1187 words)

	Data Mining
		While having varying degrees of success, the data mining tools developed thus far, by and large, share the following computational model: the tools would take some inputs from the user, then crunch away to find the patterns the tools were designed for, and at the end return some answers to the user.
		To achieve this fine division of labour, our data mining tools must provide feedback to the user frequently, incorporate user guidance in the computation, and be very efficient (as real-time as possible) to engage the user.
		Based on these principles, my data mining research has several specific technical focuses: (a) the development of tools for constraint-based mining; (b) the development of a unified model and algebra for analysis and mining; (c) performance optimization; and (d) the development of new data mining capabilities, such as outlier detection and fascicle compression.
	www.cs.ubc.ca /~rng/research/datamining/data_mining.htm (1385 words)

	Data Mining
		The ACM SIGKDD is the premier professional organization for data mining.
		If you need to find a data set for a project, there is probably something on one of these sites of potential interest.
		The UC Irvine KDD Archive This is a new archive of large data sets specifically collected for researchers in data mining and KDD to serve as a benchmark collection of data (developed under sponsorship of the National Science Foundation).
	www.stat.rutgers.edu /~madigan/datamining (768 words)

	ITworld.com - Data mining
		Data mining is a subset of business intelligence, which covers a broad range of analytics technologies.
		An OLAP data set is made up of dimensions and measures, which can then be used for queries to elicit detailed data breakdowns and information on associations among variables.
		Such an approach may be useful for test-driving data mining technology on a specific project and measuring how well the investment pays off.
	www.itworld.com /App/110/050805datamining (790 words)

	Open Directory - Computers: Software: Databases: Data Mining: Tool Vendors (Site not responding. Last check: )
		DataEngine is a software tool for data analysis in which fuzzy rules, fuzzy clustering, neural networks and fuzzy neural systems are offered in combination with mathematics, statistics and signal processing.
		Thinx Data Visualization Software - A 32bit Windows application that is becoming the standard by which users connect graphics with data.
		Data warehouse and integration, data cleansing and data mining over the web, based on open source advanced logic programming technology.
	dmoz.org /Computers/Software/Databases/Data_Mining/Tool_Vendors (1883 words)

	Elder Research: Predictive Analytics & Data Mining Consulting
		ACM Conference on Knowledge Discovery and Data Mining (KDD-2007) From Trees to Forests and Rule Sets -- A Unified Overview of Ensemble Methods, Tutorial, San Jose, CA, August 12, 2007
		ACM Conference on Knowledge Discovery and Data Mining (KDD-2006), Philadelphia, PA, August 20-23, 2006
		The principals are active researchers in Data Mining, contributing to the literature of this emerging field in books, conferences, and through highly-regarded short courses and training seminars.
	www.datamininglab.com (405 words)

	ONLamp.com -- Data Mining Email
		Data mining is a class of database applications that look for hidden patterns in a group of data.
		The objective is to data mine the email that resides in a Mozilla mail box.
		Many of the tables have a column of type oid, which refers to the actual data that is located in the system catalog pg_largeobject.
	www.onlamp.com /pub/a/onlamp/2004/04/08/datamining_email.html (859 words)

	What is data mining? - A Word Definition From the Webopedia Computer Dictionary
		A class of database applications that look for hidden patterns in a group of data that can be used to predict future behavior.
		Data mining is popular in the science and mathematical fields but also is utilized increasingly by marketers trying to distill useful consumer data from Web sites.
		Their current focus is in finding association rules and in analyzing sample sizes needed for reliable data mining.
	www.webopedia.com /TERM/D/data_mining.html (484 words)

	Statistical Data Mining Tutorials
		If you're new to data mining you'll enjoy it, but your eyebrows will raise at how simple it all is! After having defined the job of classification, we explain how information gain (next Andrew Tutorial) can be used to find predictive input attributes.
		Over a century old, this form of data mining is still being used very intensively by statisticians and machine learners alike.
		Probability For Data Mining for a more in-depth introduction to Density estimation and general use of Bayes Classifiers, with Naive Bayes Classifiers as a special case.
	www.autonlab.org /tutorials (3003 words)

	Open Directory - Computers: Software: Databases: Data Mining
		About.com on Data Mining - About.com presents a collection of original feature articles, net links, forum discussions and a chat room dedicated to data mining and data warehousing topics.
		Data Mining and Knowledge Discovery - A peer-reviewed journal publishing articles on all aspects of Knowledge Discovery in Databases (KDD) and data mining methods for extracting high-level representations (patterns and models) from data.
		Bank Of Montreal Mines Knowledge From Data - Jan Mrazek says privacy and performance are key issues in business intelligence and data mining for the Bank of Montreal.
	dmoz.org /Computers/Software/Databases/Data_Mining (531 words)

	Data Mining - Data Mining Books And Papers (Misc)
		Data Mining Techniques Michael J. Berry, Gordon S. Linoff
		Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations Ian H. Witten, Eibe Frank, Jim Gray (Editor)
		Data Mining: A Heuristic Approach Hussein Abbass, Ruhul Sarker (Editor), Charles Newton (Editor)
	www.the-data-mine.com /bin/view/Misc/DataMiningBooksAndPapers (285 words)

	ORBSEARCH.COM \| encyclopedia of knowledge
		Data mining is the practice of searching large stores of data for patterns.
		Data mining has been defined as "The nontrivial extraction of implicit, previously unknown, and potentially useful information from data" [1].
		Content is provided as is from wikipedia.org without guarantee of accuracy.
	www.orbsearch.com /da/Data_mining.php (540 words)

	SQL Server Data Mining > Home
		This site has been designed by the SQL Server Data Mining team to provide the SQL Server community with access to and information about our exciting data mining features.
		Preview new SQL 2008 features in the add-ins that allow you to take advantage of the power of SQL Server Data Mining in the familiar environment of Excel and Visio whether you are a data mining expert or a novice.
		Learn more about the new APIs for data mining in SQL Server 2005, and get an introduction to several common development scenarios.
	www.sqlserverdatamining.com (356 words)

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