Cluster analysis using data mining approach to develop CRM methodology to assess the customer loyalty Seyed Mohammad Seyed Hosseini *‚ Anahita Maleki‚ Mohammad Reza Gholamian Industrial Engineering Department‚ Iran University of Science and Technology‚ Tehran‚ Iran a r t i c l e i n f o a b s t r a c t Data mining (DM) methodology has a tremendous contribution for researchers to extract the hidden knowledge and information which have been inherited in the data used by researchers. This
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Web Mining Data mining is the nontrivial process of identifying valid novel‚ potentially useful‚ and ultimately understandable patterns in data – Fayyad. The most commonly used techniques in data mining is artificial neural networks‚ decision trees‚ genetic algorithm‚ nearest_neighbour method‚ and rule induction. Data mining research has drawn on a number of other fields such as inductive learning‚ machine learning and statistics etc. Machine learning – is the automation of a learning process
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Support Spatial Data Mining Gennady Andrienko and Natalia Andrienko GMD - German National Research Center for Information Technology Schloss Birlinghoven‚ Sankt-Augustin‚ D-53754 Germany gennady.andrienko@gmd.de http://allanon.gmd.de/and/ Abstract. Data mining methods are designed for revealing significant relationships and regularities in data collections. Regarding spatially referenced data‚ analysis by means of data mining can be aptly complemented by visual exploration of the data presented on
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1. MINING INDUSTRIES IN THE PHILIPPINES: * Luis Gonzales Jr. Mining * Goldenboys ‚Inc. * Steelfab Water Solutions Asia Inc. * Fil Edward Rey A. Manila * Mg-gelber Trading Co. * Sytenco Philippines Corporation * Maricalum Mining Corporation * Tangshan Relia Industrial Pump. Co.‚Itd Maricalum Mining Corporation (MMC) in south Negros. Having 2‚673 claims on mining in Barangays Cansauro‚ Hinablan‚ Tao-angan and Hinablan‚ of the towns of Cauayan and Sipalay‚ Negros Occidental
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Multiple Linear Regression Data Mining for Business Intelligence Shmueli‚ Patel & Bruce © Galit Shmueli and Peter Bruce 2010 Topics Explanatory vs. predictive modeling with regression Example: prices of Toyota Corollas Fitting a predictive model Assessing predictive accuracy Selecting a subset of predictors (variable selection) Explanatory Modeling Goal: Explain relationship between predictors (explanatory variables) and target Familiar use of regression in data analysis Multiple linear
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Environmental studies assignment Ques 1: Mining Mining is the extraction of valuable minerals or other geological materials from the earth. Ores recovered by mining include metals‚ coal‚ oil shale‚ gemstones‚ limestone‚ dimension stone‚ rock salt‚ potash‚ gravel‚ and clay. Mining is required to obtain any material that cannot be grown through agricultural processes‚ or created artificiallyin a laboratory or factory. Mining in a wider sense includes extraction of any non-renewable resource such as petroleum
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Accidents Due To Machinery Welcome to all Participants Trend of fatal Accidents in non -coal Mines Year Fatal Accidents 1998 61 2000 51 2002 52 2004 57 2005 48 2006 62 Accidents due to Machinery in Non – Coal Mines Year Fatal Accidents Due to Machinery 2001 71 33 2002 52 19 2003 52 21 2004 57 26 2005 48 23 2006 62 25 Causes of fatal Accidents due to Machinery‚non coal Mines in 2005 Transport machinery(winding)- nil Transport machinery(other
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Abstract Data mining is one of the most important tools for analyzing information from large databases. The retail industry has recently seen the growing number of data mining applications in reducing time and cost for the industry. The paper defines data mining and the seven operations of data mining that have been classified through many different literatures. It then focus on the important applications of data mining in retail industry including marketing‚ customer relationship management‚ risk
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Introduction: Recently‚ research in Human Resource (HR) activities that are embedded with Data Mining Techniques can solve unstructured and indistinct decision making problems. Human Resource Management (HRM) activities can facilitate to take fair and consistent decisions‚ and to improve the effectiveness of decision-making processes. Besides the challenges for HR Professionals to manage the organizational decisions and talents‚ especially they have to ensure that the selection of a right
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Role Mining - Revealing Business Roles for Security Administration using Data Mining Technology Martin Kuhlmann Dalia Shohat SYSTOR Security Solutions GmbH Hermann-Heinrich-Gossen-Strasse 3 D 50858 Cologne [martin.kuhlmann|dalia.shohat] @systorsecurity.com Gerhard Schimpf SMF TEAM IT-Security Consulting Am Waldweg 23 D 75173 Pforzheim Gerhard.Schimpf@smfteam.de ABSTRACT In this paper we describe the work devising a new technique for role-finding to implement Role-Based Security Administration
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