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"KDD" redirects here. For the Japanese telecommunications company, see
KDDI.
.^ That is, data mining attempts to extract knowledge from data.- AITopics / DataMining 19 January 2010 18:018 UTC www.aaai.org [Source type: Academic]
^ Understand the data mining process.- Data mining, data mining course, graduate data mining, financial data mining, machine learning, neural networks, genetic programs, decision trees, WEKA 19 January 2010 18:018 UTC sce.uhcl.edu [Source type: Academic]
^ Data mining is a knowledge discovery process.
.^ For more information on Data Mining .- Predicting Customer Profitability – A First Data Mining Model 19 January 2010 18:018 UTC technet.microsoft.com [Source type: FILTERED WITH BAYES]
^ Question: Why is data mining important?
^ Data mining is a tool, not a magic wand.- welcome to Hua Analytical Technology Co.,Ltd����Data Mining 19 January 2010 18:018 UTC www.huaat.com [Source type: FILTERED WITH BAYES]
.^ Their products are used in a wide range of industries, including power generation, pulp and paper, food and beverage, chemical processing, marine, materials processing, medical, financial, targeted marketing, credit, and securities. .- PC AI - Data Warehouse and Data Mining 19 January 2010 18:018 UTC www.pcai.com [Source type: Academic]
^ We study the underlying principles of data analysis algorithms, develop innovative techniques for knowledge discovery, and apply those techniques to practical tasks in areas such as fraud detection, scientific data analysis, and web mining."- AITopics / DataMining 19 January 2010 18:018 UTC www.aaai.org [Source type: Academic]
^ The stored data can be of a wide nature, such as oil-drilling data, stock market data, consumer data, etc.- Data Mining: Extending the Information Warehouse Framework 19 January 2010 18:018 UTC www.almaden.ibm.com [Source type: Reference]
.^ All the data preparation and mining is carried out on the client.- XpertRule | White Papers | Data Mining - Beyond Algorithms 19 January 2010 18:018 UTC www.xpertrule.com [Source type: Academic]
^ Rule induction data mining was used to discover patterns in the data.- XpertRule | White Papers | Data Mining - Beyond Algorithms 19 January 2010 18:018 UTC www.xpertrule.com [Source type: Academic]
^ Data Mining (DM), also called Knowledge-Discovery in Databases (KDD) or Knowledge-Discovery and Data Mining, is the process of automatically searching large volumes of data for patterns such as association rules.
.^ Understand the data mining process.- Data mining, data mining course, graduate data mining, financial data mining, machine learning, neural networks, genetic programs, decision trees, WEKA 19 January 2010 18:018 UTC sce.uhcl.edu [Source type: Academic]
^ Data mining is a knowledge discovery process.
^ Data Mining (DM), also called Knowledge-Discovery in Databases (KDD) or Knowledge-Discovery and Data Mining, is the process of automatically searching large volumes of data for patterns such as association rules.
.^ The patterns data mining finds for those two goals may be very different.- welcome to Hua Analytical Technology Co.,Ltd����Data Mining 19 January 2010 18:018 UTC www.huaat.com [Source type: FILTERED WITH BAYES]
^ Data mining provides the enterprise with intelligence.- Data Mining and Statistics: What is the Connection? 19 January 2010 18:018 UTC www.tdan.com [Source type: FILTERED WITH BAYES]
^ Data mining News - IT Industry Today This is a service of a digital news provider .- Data mining News - IT Industry Today 19 January 2010 18:018 UTC it.einnews.com [Source type: News]
.^ A variety of data sources may be used to form the base of data to be mined.- Data Mining: Extending the Information Warehouse Framework 19 January 2010 18:018 UTC www.almaden.ibm.com [Source type: Reference]
^ September 21, 2005 Lawmakers are full of questions about a data-mining effort that may have compiled information on Mohammed Atta before the attacks.- data mining news on CNET 19 January 2010 18:018 UTC ces.cnet.com [Source type: General]
^ This tutorial can be used as a self-contained introduction to the flavor and terminology of data mining without needing to review many statistical or probabilistic pre-requisites.- Statistical Data Mining Tutorials 19 January 2010 18:018 UTC www.autonlab.org [Source type: FILTERED WITH BAYES]
.^ Comparing data sub-sets with K-Means .
^ Data Mining (DM), also called Knowledge-Discovery in Databases (KDD) or Knowledge-Discovery and Data Mining, is the process of automatically searching large volumes of data for patterns such as association rules.
^ Data mining is the automated analysis of large data sets to find patterns and trends that might otherwise go undiscovered.- Advanced Data Mining - CIO.com - Business Technology Leadership 19 January 2010 18:018 UTC www.cio.com [Source type: General]
.^ Data Mining (DM), also called Knowledge-Discovery in Databases (KDD) or Knowledge-Discovery and Data Mining, is the process of automatically searching large volumes of data for patterns such as association rules.
^ A data item whose value falls outside the bounds enclosing most of the other corresponding values in the sample.- An Introduction to Data Mining 19 January 2010 18:018 UTC www.thearling.com [Source type: FILTERED WITH BAYES]
^ In other words, if you had 1,000 rows of data, you would build a sample of 1,000 rows by picking one row at random.- Two Crows white paper: "Scalable Data Mining" 19 January 2010 18:018 UTC www.twocrows.com [Source type: FILTERED WITH BAYES]
.^ A variety of data sources may be used to form the base of data to be mined.- Data Mining: Extending the Information Warehouse Framework 19 January 2010 18:018 UTC www.almaden.ibm.com [Source type: Reference]
^ Q. What are some of the different techniques used in data mining?
^ Many times we see that data mining operators can be used cooperatively.- Data Mining: Extending the Information Warehouse Framework 19 January 2010 18:018 UTC www.almaden.ibm.com [Source type: Reference]
.^ Focus on large data sets and databases .
^ It helps in extracting data from both software and hardware platforms and can be applied on new systems in order to develop the new products and upgrade the existing platforms.- Data Mining Research Services-Web Projects and Internet Database Mining-Data Mine Applications 19 January 2010 18:018 UTC www.dataentrysolution.com [Source type: FILTERED WITH BAYES]
^ Advances in information technology and data collection methods have led to the availability of large data sets in commercial enterprises and in a wide variety of scientific and engineering disciplines.- Data Mining Conference 2004 19 January 2010 18:018 UTC www.siam.org [Source type: Academic]
Background
.^ Data Mining (DM), also called Knowledge-Discovery in Databases (KDD) or Knowledge-Discovery and Data Mining, is the process of automatically searching large volumes of data for patterns such as association rules.
^ Solving the Challenges of Exponential Data Growth sponsored by Syncsort WHITE PAPER - This paper explores the reasons why data volumes are increasing and where bottlenecks most frequently occur.
^ Data mining is the automated analysis of large data sets to find patterns and trends that might otherwise go undiscovered.- Advanced Data Mining - CIO.com - Business Technology Leadership 19 January 2010 18:018 UTC www.cio.com [Source type: General]
.^ Descriptive It identifies patterns or relationships in data.
^ Data mining is the automated analysis of large data sets to find patterns and trends that might otherwise go undiscovered.- Advanced Data Mining - CIO.com - Business Technology Leadership 19 January 2010 18:018 UTC www.cio.com [Source type: General]
^ Data mining is the practice of automatically searching large stores of data to discover patterns and trends that go beyond simple analysis.
.^ Advances in information technology and data collection methods have led to the availability of large data sets in commercial enterprises and in a wide variety of scientific and engineering disciplines.- Data Mining Conference 2004 19 January 2010 18:018 UTC www.siam.org [Source type: Academic]
^ The rapid growth of computerized data, and the computer power available to analyze it, creates great opportunities for data mining in business, medicine, science, government, etc.- Statistics 36-350: Data Mining (Fall 2009) 19 January 2010 18:018 UTC www.stat.cmu.edu [Source type: Academic]
^ Fortunately, we have reached a point in terms of computational power, storage capacity and cost that enables us to gather, analyze and mine unprecedented amounts of data.- Two Crows white paper: "Scalable Data Mining" 19 January 2010 18:018 UTC www.twocrows.com [Source type: FILTERED WITH BAYES]
.^ Data Mining (DM), also called Knowledge-Discovery in Databases (KDD) or Knowledge-Discovery and Data Mining, is the process of automatically searching large volumes of data for patterns such as association rules.
^ The IDU Data Mining (DM) technical area is about techniques for processing and combining raw data -- from large, distributed, heterogeneous, multidimensional data sets with complex spatial and/or temporal dynamics -- to detect patterns and regularities.- AITopics / DataMining 19 January 2010 18:018 UTC www.aaai.org [Source type: Academic]
^ Data mining is the automated analysis of large data sets to find patterns and trends that might otherwise go undiscovered.- Advanced Data Mining - CIO.com - Business Technology Leadership 19 January 2010 18:018 UTC www.cio.com [Source type: General]
.^ Support Vector Machines (20 November).- Statistics 36-350: Data Mining (Fall 2009) 19 January 2010 18:018 UTC www.stat.cmu.edu [Source type: Academic]
^ This study does highlight the fact that a chosen option does not necessarily dictate or limit the scale as long as the other attributes such as an effective parallelism algorithm, B-tree indices, main-memory computation, compression etc.- The Data Mining Renaissance – GigaOM 19 January 2010 18:018 UTC gigaom.com [Source type: General]
^ It is a fairly recent topic in computer science but applies many older computational techniques from statistics, information retrieval, machine learning and pattern recognition.
.^ There are a number of data mining methods.- Data Mining: Extending the Information Warehouse Framework 19 January 2010 18:018 UTC www.almaden.ibm.com [Source type: Reference]
^ Data Mining applied to File Integrity.- Security Issues in Data Mining 19 January 2010 18:018 UTC www.cs.purdue.edu [Source type: Academic]
^ Understand the data mining process.- Data mining, data mining course, graduate data mining, financial data mining, machine learning, neural networks, genetic programs, decision trees, WEKA 19 January 2010 18:018 UTC sce.uhcl.edu [Source type: Academic]
^{[1]} .^ December 5, 2006 Department of Homeland Security implements data-mining system for passengers traveling to the U.S. TAGS: risk assessment , data mining , passenger , European Union , agency , government , U.S. Yahoo focuses on research .- data mining news on CNET 19 January 2010 18:018 UTC ces.cnet.com [Source type: General]
^ Instead, the underlying data will be available to anyone who wants to build a superior site or tool to sift through it.- Congressional Data Mining: Coming Soon? | Mother Jones 19 January 2010 18:018 UTC motherjones.com [Source type: FILTERED WITH BAYES]
^ Data Mining (DM), also called Knowledge-Discovery in Databases (KDD) or Knowledge-Discovery and Data Mining, is the process of automatically searching large volumes of data for patterns such as association rules.
.^ Data-mining sucks: official report .- Data-mining sucks: official report - Boing Boing 19 January 2010 18:018 UTC www.boingboing.net [Source type: General]
^ Data mining: Life after report generators.- Bibliomining Bibliography (data mining in libraries) 19 January 2010 18:018 UTC bibliomining.com [Source type: Academic]
^ Extracting that information and getting it into usable shape, however, requires sophisticated data mining tools.- Data mining | ITworld 19 January 2010 18:018 UTC www.itworld.com [Source type: General]
.^ This tutorial can be used as a self-contained introduction to the flavor and terminology of data mining without needing to review many statistical or probabilistic pre-requisites.- Statistical Data Mining Tutorials 19 January 2010 18:018 UTC www.autonlab.org [Source type: FILTERED WITH BAYES]
^ Data mining and Knowledge Discovery selects a collection of methods from a branch of Artificial Intelligence that began its explosive growth very recently.
^ Data mining is the automated analysis of large data sets to find patterns and trends that might otherwise go undiscovered.- Advanced Data Mining - CIO.com - Business Technology Leadership 19 January 2010 18:018 UTC www.cio.com [Source type: General]
.^ Intelligent applications, such as neural networks and genetic algorithms are ideal for finding trends and unknown information from the vast quantities of computer data.- PC AI - Data Warehouse and Data Mining 19 January 2010 18:018 UTC www.pcai.com [Source type: Academic]
.^ Comparing data sub-sets with K-Means .
^ Domain-specific data-mining solutions .- AITopics / DataMining 19 January 2010 18:018 UTC www.aaai.org [Source type: Academic]
^ Although most of the data mining techniques have existed, at least as academic algorithms, for years or decades, it is only in the last several years that commercial data mining has caught on in a big way.- Data Mining and Statistics: What is the Connection? 19 January 2010 18:018 UTC www.tdan.com [Source type: FILTERED WITH BAYES]
.^ Models and issues in data stream systems .
^ A variety of data sources may be used to form the base of data to be mined.- Data Mining: Extending the Information Warehouse Framework 19 January 2010 18:018 UTC www.almaden.ibm.com [Source type: Reference]
^ Then, in May 2006, an event happened that in one day demonstrated convincingly that our approach was significantly better than all the other alternatives in our field.
In these situations, inherent correlations can be either controlled for, or removed altogether, during the construction of the
experimental design.
.^ There are a number of data mining methods.- Data Mining: Extending the Information Warehouse Framework 19 January 2010 18:018 UTC www.almaden.ibm.com [Source type: Reference]
^ The CRISP-DM process model .- Data mining, data mining course, graduate data mining, financial data mining, machine learning, neural networks, genetic programs, decision trees, WEKA 19 January 2010 18:018 UTC sce.uhcl.edu [Source type: Academic]
^ Understand the data mining process.- Data mining, data mining course, graduate data mining, financial data mining, machine learning, neural networks, genetic programs, decision trees, WEKA 19 January 2010 18:018 UTC sce.uhcl.edu [Source type: Academic]
.^ These capabilities are now evolving to integrate directly with industry-standard data warehouse and OLAP platforms.- An Introduction to Data Mining 19 January 2010 18:018 UTC www.thearling.com [Source type: FILTERED WITH BAYES]
.^ Responses to “The process of data mining” .
^ The process of data mining HOME .
^ Understand the data mining process.- Data mining, data mining course, graduate data mining, financial data mining, machine learning, neural networks, genetic programs, decision trees, WEKA 19 January 2010 18:018 UTC sce.uhcl.edu [Source type: Academic]
.^ Models and issues in data stream systems .
^ Link mining includes both descriptive and predictive modeling of link data.- UT-Austin Data Mining Seminar Schedule Abstracts 19 January 2010 18:018 UTC www.cs.utexas.edu [Source type: Academic]
^ Three applications of data mining principles .- UT-Austin Data Mining Seminar Schedule Abstracts 19 January 2010 18:018 UTC www.cs.utexas.edu [Source type: Academic]
.^ Many forms of data mining are predictive.
^ Thus data mining technique is developed based on the knowledge based concepts.
^ Client based data mining .- XpertRule | White Papers | Data Mining - Beyond Algorithms 19 January 2010 18:018 UTC www.xpertrule.com [Source type: Academic]
PMML version 4.0 was released in June 2009.
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Research and evolution
.^ These findings are documented in Digital Exposure , an article by Elizabeth Svoboda published in the November 2009 issue of Discover .- How to Protect Yourself Against Data Mining | Small Business Trends 19 January 2010 18:018 UTC smallbiztrends.com [Source type: General]
^ By far the most important negative for decision trees is that they are forced to make decisions along the way based on limited information that implicitly leaves out of consideration the vast majority of potential rules in the training file.- New Technology | Data Mining Technologies Inc. 19 January 2010 18:018 UTC www.data-mine.com [Source type: FILTERED WITH BAYES]
^ This Special Issue will provide a significant opportunity for authors to publish important novel and original contributions in the area of Data Mining applied to Social Media.
^{[5]}
.^ That is, data mining attempts to extract knowledge from data.- AITopics / DataMining 19 January 2010 18:018 UTC www.aaai.org [Source type: Academic]
^ ACM's Special Interest Group on Knowledge Discovery and Data Mining (SIGKDD) : A premier group promoting knowledge discovery R&D. Organizes one of the top conferences in the area.- Data mining, data mining course, graduate data mining, financial data mining, machine learning, neural networks, genetic programs, decision trees, WEKA 19 January 2010 18:018 UTC sce.uhcl.edu [Source type: Academic]
^ Data Mining and Knowledge Discovery : journal edited by Usama Fayyad.- Data mining, data mining course, graduate data mining, financial data mining, machine learning, neural networks, genetic programs, decision trees, WEKA 19 January 2010 18:018 UTC sce.uhcl.edu [Source type: Academic]
^{[citation needed]} Since 1989 they have hosted an annual international conference and published its proceedings,
^{[6]} and since 1999 have published a biannual
academic journal titled "SIGKDD Explorations".
^{[7]} Other Computer Science conferences on data mining include:
Process
.^ This process of using computers to extract useful information from a database is called "knowledge discovery," or simply data mining.
^ Data mining is also known as Knowledge Discovery in Data ( KDD).
^ It is a process to find the hidden information in a database.
.^ There are a number of data mining methods.- Data Mining: Extending the Information Warehouse Framework 19 January 2010 18:018 UTC www.almaden.ibm.com [Source type: Reference]
^ Understand the data mining process.- Data mining, data mining course, graduate data mining, financial data mining, machine learning, neural networks, genetic programs, decision trees, WEKA 19 January 2010 18:018 UTC sce.uhcl.edu [Source type: Academic]
^ Data mining is a knowledge discovery process.
^{[10]}
Pre-processing
.^ Data Mining (DM), also called Knowledge-Discovery in Databases (KDD) or Knowledge-Discovery and Data Mining, is the process of automatically searching large volumes of data for patterns such as association rules.
^ MapReduce is a technique popularized by Google that distributes complex problems to many distributed nodes and, as such, is useful for processing information from large data sets.- The Data Mining Renaissance – GigaOM 19 January 2010 18:018 UTC gigaom.com [Source type: General]
^ Fayyad, Usama, et al., The KDD Process for Extracting Useful Knowledge from Volumes of Data , Communications of the ACM , 39 11, November 1996.- Data mining, data mining course, graduate data mining, financial data mining, machine learning, neural networks, genetic programs, decision trees, WEKA 19 January 2010 18:018 UTC sce.uhcl.edu [Source type: Academic]
.^ By and large, the application of data mining is constrained only by our imagination.- Predicting Customer Profitability – A First Data Mining Model 19 January 2010 18:018 UTC technet.microsoft.com [Source type: FILTERED WITH BAYES]
^ This tutorial can be used as a self-contained introduction to the flavor and terminology of data mining without needing to review many statistical or probabilistic pre-requisites.- Statistical Data Mining Tutorials 19 January 2010 18:018 UTC www.autonlab.org [Source type: FILTERED WITH BAYES]
^ MWF 10:30--11:20 Porter Hall 226B Data mining is the art of extracting useful patterns from large bodies of data; finding seams of actionable knowledge in the raw ore of information.- Statistics 36-350: Data Mining (Fall 2009) 19 January 2010 18:018 UTC www.stat.cmu.edu [Source type: Academic]
.^ Hive , for example, is an open-source data warehouse infrastructure built on top of Hadoop.- The Data Mining Renaissance – GigaOM 19 January 2010 18:018 UTC gigaom.com [Source type: General]
^ Because these issues are common with those found while building Data Warehouses, we will not discuss them here.- Data Mining: Extending the Information Warehouse Framework 19 January 2010 18:018 UTC www.almaden.ibm.com [Source type: Reference]
The target set is then cleaned.
.^ Resolving semantic ambiguities, handling missing values in data and cleaning dirty data sets are typical data integration issues.- Data Mining: Extending the Information Warehouse Framework 19 January 2010 18:018 UTC www.almaden.ibm.com [Source type: Reference]
^ First, pixels are labeled as either background or as significant pixels; this is done to remove noise from the data.
.^ I calculate average age of the 5 tables without combining them into one big data table.- Data-Mi.ning - The aim of data mining is to make sense of large amounts of data 19 January 2010 18:018 UTC data-mi.ning.com [Source type: General]
^ Turning nonlinear problems into linear ones by expanding into high-dimensional feature spaces.- Statistics 36-350: Data Mining (Fall 2009) 19 January 2010 18:018 UTC www.stat.cmu.edu [Source type: Academic]
^ Thus, with over 20,000 observations per shift, there is a tremendous amount of data.- Two Crows white paper: "Scalable Data Mining" 19 January 2010 18:018 UTC www.twocrows.com [Source type: FILTERED WITH BAYES]
A feature vector is a summarised version of the raw data observation.
.^ First, the dates of all the time-series were turned into bits / date-binaries and invalid raw data was excluded.- Assembly Language Extensions of Visual Prolog For Data Mining 19 January 2010 18:018 UTC omadeon.com [Source type: FILTERED WITH BAYES]
^ GooglingSEO says: November 8, 2009 at 10:23 pm How to Protect Yourself Against Data Mining http://bit.ly/1noa0o .- How to Protect Yourself Against Data Mining | Small Business Trends 19 January 2010 18:018 UTC smallbiztrends.com [Source type: General]
^ The driving force for data mining is the presence of petabyte-scale online archives that potentially contain valuable bits of information hidden in them.- Data mining, data mining course, graduate data mining, financial data mining, machine learning, neural networks, genetic programs, decision trees, WEKA 19 January 2010 18:018 UTC sce.uhcl.edu [Source type: Academic]
.^ Turning nonlinear problems into linear ones by expanding into high-dimensional feature spaces.- Statistics 36-350: Data Mining (Fall 2009) 19 January 2010 18:018 UTC www.stat.cmu.edu [Source type: Academic]
.^ The process of data mining .
^ Data mining is a knowledge discovery process.
^ Responses to “The process of data mining” .
.^ Data mining and Knowledge Discovery selects a collection of methods from a branch of Artificial Intelligence that began its explosive growth very recently.
^ Featured Listings Data Mining Demo Watch the Cognos Data Mining Software Demo Right Now.- Data Mining Software Information | Business.com 19 January 2010 18:018 UTC www.business.com [Source type: Academic]
^ The following list summarizes those features of a data mining tool that make it scalable.- Two Crows white paper: "Scalable Data Mining" 19 January 2010 18:018 UTC www.twocrows.com [Source type: FILTERED WITH BAYES]
.^ If you don't use different training and test data, the accuracy of the model will be overestimated.- Two Crows white paper: "Scalable Data Mining" 19 January 2010 18:018 UTC www.twocrows.com [Source type: FILTERED WITH BAYES]
^ In this method, we randomly divide the data into two equal sets.- Two Crows white paper: "Scalable Data Mining" 19 January 2010 18:018 UTC www.twocrows.com [Source type: FILTERED WITH BAYES]
^ Data Mining (DM), also called Knowledge-Discovery in Databases (KDD) or Knowledge-Discovery and Data Mining, is the process of automatically searching large volumes of data for patterns such as association rules.
Data mining
Data mining commonly involves four classes of tasks:^{[10]}
.