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    • Information enhancement for data mining WIREs Data

      Information enhancement techniques are desired in many areas such as data mining, machine learning, business intelligence, and web data analysis.

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    • Signal enhancement and data mining for biological and

      Mass spectrometry has been actively involved in the areas of healthcare, pharmaceutics, environmental analysis, food industry and forensics due to its ability to provide molecular information at trace levels. Recently, because of the complexity of chemical and biological samples, computer assisted mass spectra analysis, including signal enhancement, statistics and machine learning, has been

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    • NVD Control AC 23 DATA MINING PROTECTION

      Supplemental Guidance Data storage objects include, for example, databases, database records, and database fields. Data mining prevention and detection techniques include, for example (i) limiting the types of responses provided to database queries; (ii) limiting the number/frequency of database queries to increase the work factor needed to determine the contents of such databases; and (iii

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    • Data Mining Based Accuracy Enhancement Of ANN IJCCTS

      Data mining is the process of analyzing data from different viewpoints and abridgment it into useful information, information that can be used to add to profits, cuts costs, or

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    • Department of Homeland Security

      employ data mining in a manner that both supports the Departments mission to protect the homeland and protects privacy. Pursuant to congressional requirements,

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    • Version 9 Features Statistica

      Data Mining Enhancements Data Miner Recipes STATISTICA 9 features the long awaited final release of Data Miner Recipes (DMR), previously available only as a beta release. DMR is an easy and flexible step by step data mining guide, and it is now available to all of StatSofts data miner customers.

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    • Expectation Maximization Oracle

      The Oracle Data Mining implementation includes significant enhancements, such as scalable processing of large volumes of data and automatic parameter initialization. The strategies that Oracle Data Mining uses to address the inherent limitations of EM clustering are described further in this section.

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    • Data mining for yield enhancement in semiconductor

      Data mining is defined to be the exploration and analysis, by automatic or semiautomatic means, of large quantities of data stored either in databases, data warehouses, or other information repositories to discover interesting knowledge including meaningful patterns and rules (Berry and Linoff, 1997, Han and Kamber, 2001). Therefore, data

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    • Version 9 Features Statistica

      Data Mining Enhancements Data Miner Recipes STATISTICA 9 features the long awaited final release of Data Miner Recipes (DMR), previously available only as a beta release. DMR is an easy and flexible step by step data mining guide, and it is now available to all of StatSofts data miner customers.

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    • PERFORMANCE ENHANCEMENT OF WEKA THE DATA MINING

      Data mining is an analytic process designed to explore data in search of consistent patterns and/or systematic relationships between variables, and then to validate the findings by

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    • DealActivator Announces Soft Credit Pull Reporting and

      Dominion Dealer Solutions is an industry leader in equity data mining, automotive marketing, CRM, responsive web design, lead generation, reputation and inventory management.

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    • Information enhancement for data mining Zhang 2011

      Information enhancement techniques are desired in many areas such as data mining, machine learning, business intelligence, and web data analysis.

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    • What is data mining? Definition from WhatIs

      Data mining is the process of sorting through large data sets to identify patterns and establish relationships to solve problems through data analysis. Data mining tools allow enterprises to predict future trends. Read an exclusive interview with Andrew Burt, chief privacy offer and legal engineer

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    • SAS Enterprise Miner and SAS Factory Miner Customer

      SAS Enterprise Miner, SAS Factory Miner, and SAS High Peformance Data Mining product page on the Support Site has the latest news, samples, downloads, support information, training, and documentation.

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    • Richard Lees on BI Data Mining as an Enhancement to

      May 07, 20090183;32;Essentially, you ask the data mining to create a model to predict products, based on other products (and other variables such as time of day, store, customer gender etc). The data mining algorithms can scan billions of transactions and produce a data mining model in a relatively short time.

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    • Data mining

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

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    • Data Mining Enhancements in the November CTP of SQL Server

      Dec 02, 20070183;32;From Raman Iyers great website on SQL Server Data Mining here are some of the new Data Mining Improvements in SQL Server 2008 November CTP.The November Community Technology Preview of SQL Server 2008. has just been released and it includes major data mining improvements 183; The Microsoft Time Series algorithm has been enhanced to include ARIMA in addition to the existing

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    • What is data mining? SAS

      Data mining is the process of finding anomalies, patterns and correlations within large data sets to predict outcomes. Using a broad range of techniques, you can use this information to increase revenues, cut costs, improve customer relationships, reduce risks and more.

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    • DealActivator Announces Soft Credit Pull Reporting and

      Mar 23, 20160183;32;Dominion Dealer Solutions is an industry leader in equity data mining, automotive marketing, CRM, responsive web design, lead generation, reputation and inventory management. In 2015, DealActivator released Soft Credit Pull functionality to help dealers achieve conquest sales through equity opportunities in the service drive.

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    • AC 23 DATA MINING PROTECTION STIG Viewer

      Data mining prevention and detection techniques include, for example (i) limiting the types of responses provided to database queries; (ii) limiting the number/frequency of database queries to increase the work factor needed to determine the contents of such databases; and (iii) notifying organizational personnel when atypical database queries

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    • DATA MINING FOR TEACHING AND LEARNING EFFECTIVENESS

      It is a data mining research project that contributes to improve teaching and learning effectiveness within academic institutions by exploiting intelligent algorithm on collected databases for

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    • Information enhancement for data mining WIREs Data

      Information enhancement techniques are desired in many areas such as data mining, machine learning, business intelligence, and web data analysis.

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    • Mining Educational Data to Analyze Students Performance

      Data mining in higher education is a recent research field and this area of research is gaining popularity because of its potentials to educational institutes.

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    • Richard Lees on BI Data Mining as an Enhancement to

      May 07, 20090183;32;Essentially, you ask the data mining to create a model to predict products, based on other products (and other variables such as time of day, store, customer gender etc). The data mining algorithms can scan billions of transactions and produce a data mining model in a relatively short time.

      Contact Us
    • 2013 UltraTax CS Data Mining EnhancementsIncluding

      2013 UltraTax CS Data Mining EnhancementsIncluding Ability to Proforma Reports Thomson Reuters Tax amp; Accounting CS Tax amp; Asset Management Solutions March 18, 2014 Data mining is a versatile tool that lets you search your UltraTax CS product databases for clients with specific characteristics.

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    • Information enhancement for data mining WIREs Data

      Information enhancement techniques are desired in many areas such as data mining, machine learning, business intelligence, and web data analysis.

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    • Model Enhancement in Data Mining Calibration, ROC

      Model Enhancement in Data Mining Calibration, ROC Analysis, Model Combination and Mimetic Models Jos233; Hern225;ndez Orallo Rome, 18th May 2009. Dpto. de Sistemas Inform225;ticos y Computaci243;n, Universidad Polit233;cnica de Valencia, Model enhancement is an option which tries to

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    • Information enhancement for data mining DeepDyve

      Information enhancement for data mining Information enhancement for data mining Zhang, Shichao 2011 07 01 000000 Information enhancement techniques are desired in many areas such as data mining, machine learning, business intelligence, and web data analysis. Information enhancement mainly includes the following topics data cleaning, data preparation and transformation, missing values

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    • Information enhancement for data mining dl.acm

      Information enhancement techniques are desired in many areas such as data mining, machine learning, business intelligence, and web data analysis.

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    • GlobalData Mining Intelligence Center New Enhancements

      Our GlobalData Mining Intelligence Center is an interactive subscription platform that provides unparalleled and continuously updated mine and project, commodity, customer and competitor intelligence for the global mining industry. Our insights are rooted in unique data, expert analysis and innovative tools that give you a detailed view and understanding of the mining and commodity markets

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