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data mining: concepts and techniques ppt

Extract interesting and useful knowledge from the data. This data mining method helps to classify data in different classes. BIRCH Zhang, T., Ramakrishnan, R., and. The PowerPoint PPT presentation: "Data Mining: Concepts and Techniques" is the property of its rightful owner. The previous guide 10 facts on data mining for an academic research project must have given you a comprehensive outlook on data mining … Welcome! ???? Conf. They are all artistically enhanced with visually stunning color, shadow and lighting effects. In this Topic, we are going to Learn about the Data mining Techniques, As the advancement in the field of Information technology has to lead to a large number of databases in various areas. Idiot's, 7. Topics will range from statistics to machine learning to database, with a focus on analysis of large data sets. ??? 1. (A Study of Applying Text Mining for Big Data in Digital Humanities), - (A Study of Applying Text Mining for Big Data in Digital Humanities), - CIS664-Knowledge Discovery and Data Mining Data Warehousing and OLAP Technology Vasileios Megalooikonomou Dept. Clustering: Clustering analysis is a data mining technique to identify data … 9. DM is smoothly integrated into a DB/DW system. This book is referred as the knowledge discovery from data (KDD). Assimilate various black-box techniques like Neural Networks, SVM and present your findings with attractive Data Visualization techniques. Perform Text Mining to enable Customer Sentiment Analysis. Although advances in data mining technology have made extensive data collection much easier, it's still evolving and there is a constant need for new techniques and tools that can help us transform this data … Or use it to create really cool photo slideshows - with 2D and 3D transitions, animation, and your choice of music - that you can share with your Facebook friends or Google+ circles. PPT – Data Mining Concepts and Techniques PowerPoint. Data Mining: Concepts and Techniques By Akannsha A. Totewar Professor at YCCE, Wanadongari, Nagpur.1 Data Mining: Concepts and Techniques November 24, 2012 ... Making Decisions Data Presentation Business Analyst Visualization Techniques Data Mining Data Information Discovery Analyst Data … Data mining 1. View and Download PowerPoint Presentations on Data Mining Concepts And Techniques Chapter 4 PPT. اسلاید 1: January 3, ... 1/2 graduate student + 1/2 instructor teaching12-13th week: full student graduate project presentationCourse evaluation:presentation (quality of presentation slides 7% + presentation 8%) 15%midterm exam 35%project (presentation … Do not copy! To Sensor Networks, - Welcome! So while data mining needs machine learning, machine learning doesn’t necessarily need data mining. Data Analytics Using Python And R Programming (1) - this certification program provides an overview of how Python and R programming can be employed in Data Mining of structured (RDBMS) and unstructured (Big Data) data. ISBN 978-0123814791 “ We are living in the data … RDBMS, advanced data models (extended-relational. Data Warehouse and Data Mining Jiawei Han, Micheline Kamber, and Jian Pei … ppt on data mining concepts and techniques; ppt on data mining primitives; ppt on data preprocessing; ppt on data warehouse; ppt on internet protocol; ppt on internet; ppt on osi model; ppt on databases and dbms; ppt on dbms; ppt on erp; ppt on foster wheeler boiler; ppt on inert gas system; ppt on is-lm model; ppt on ism codes; ppt … Data Mining: Concepts and T ec hniques Jia w ei Han and Mic heline Kam ber Simon F raser Univ ersit y Note: This man uscript is based on a forthcoming b o ok b y Jia w ei Han and Mic heline Kam b er, c 2000 (c) Morgan Kaufmann Publishers. Gene sequence mining approximate patterns are, How to derive efficient approximate pattern, What are the possible kinds of constraints? B., Some methods for, 12. Classification is the process of finding a model that describes the data classes or concepts. Data mining is a field of intersection of computer science and statistics used to discover patterns in the information bank. This book is referred as the knowledge discovery from data (KDD). Journals IEEE-TKDE, ACM-TODS/TOIS, JIIS, J. ACM. Conferences Machine learning (ML), AAAI, IJCAI, Journals WWW Internet and Web Information. Data Mining - Tasks - Data mining deals with the kind of patterns that can be mined. Machine learning, on the other hand, refers to a group of techniques used by data scientists that allow computers to learn from data. Chapter 3. Data Mining: Concepts and Techniques provides the concepts and techniques in processing gathered data or information, which will be used in various applications. Data Mining: Concepts and Techniques 3rd Edition Solution Manual Jiawei Han, Micheline Kamber, Jian Pei The University of Illinois at Urbana-Champaign Simon Fraser University Version January 2, 2012 ⃝c Morgan Kaufmann, 2011 For Instructors’ references only. Data Mining is an information extraction activity whose goal is to discover hidden facts contained in databases. 8. Wang Last modified by: heg Created Date: 12/1/1999 10:01:55 PM Document presentation format: 如螢幕大小 Company: PU Other titles: Times New Roman Tahoma Wingdings 新細明體 Blends Microsoft Clip Gallery Data Mining: Concepts and Techniques Introduction Why Data Mining? The increasing volume of data in modern business and science calls for more complex and sophisticated tools. DragonStar 2010: Data Mining and Appl. Data Mining Concepts and Techniques Chapter 10 1031 Mining Text and Web Data I Jiawei Han and Micheline Kamber Department of Computer Science – A free PowerPoint PPT presentation display… Assimilate various black-box techniques like Neural Networks, SVM and present your findings with attractive Data Visualization techniques. Jiawei Han and Micheline Kamber, Data Mining: Concepts and Techniques, The Morgan Kaufmann Series in Data Management Systems, Jim Gray, Series Editor. visualization and computer, S. Chakrabarti. Data Mining Concepts and Techniques 3rd Edition Han Solutions Manual. - this certification program provides an overview of how Python and R programming can be employed in Data Mining of structured (RDBMS) and unstructured (Big Data) data. Data Mining: Data mining in general terms means mining or digging deep into data which is in different forms to gain patterns, and to gain knowledge on that pattern.In the process of data mining, large data sets are first sorted, then patterns are identified and relationships are established to perform data analysis and solve problems. If so, share your PPT presentation slides online with PowerShow.com. The Morgan Kaufmann Series in Data Management Systems Morgan Kaufmann Publishers, July 2011. Knowledge, S. M. Weiss and N. Indurkhya, Predictive Data, Data mining Discovering interesting patterns, A natural evolution of database technology, in, A KDD process includes data cleaning, data. Conference proceedings CHI, ACM-SIGGraph, etc. This step includes analyzing business requirements, defining the scope of the problem, defining the metrics by which the model will be evaluated, and defining specific objectives for the data mining project. ii. Avoiding False Discoveries: A completely new addition in the second edition is a chapter on how to avoid false discoveries and produce valid results, which is novel among other contemporary textbooks on data mining. Authoritative, 11. It discusses the ev olutionary path of database tec hnology whic h led up to the need for data mining, and the imp ortance of its application p oten tial. The present paper follows this tradition by discussing two different data mining techniques that are being … Other pattern-directed or statistical analyses, 2. Characterization, discrimination, association, Multiple/integrated functions and mining at, Database-oriented, data warehouse (OLAP), machine, Retail, telecommunication, banking, fraud, Different views lead to different classifications, Application view Kinds of applications adapted, Database-oriented data sets and applications, Advanced data sets and advanced applications. The Morgan Kaufmann Series in Data Management Systems Morgan Kaufmann Publishers, July 2011. Phone call model destination of the call, Analysts estimate that 38 of retail shrink is, relevant prior knowledge and goals of application, Creating a target data set data selection, Data cleaning and preprocessing (may take 60 of, Find useful features, dimensionality/variable. Data Mining: Concepts and Techniques. How to find high quality approximate patterns?? — Chapter 8 — Jiawei Han, Micheline Kamber, and Jian Pei University of Illinois at Urbana-Champaign & Simon Fraser University ©2011 Han, Kamber & Pei. - This certification program provides an overview of how Python and R programming can be employed in Data Mining of structured (RDBMS) and unstructured (Big Data) data. Or use it to upload your own PowerPoint slides so you can share them with your teachers, class, students, bosses, employees, customers, potential investors or the world. What types of relation… Introduction . Specifically, it explains data mining and the tools used in discovering knowledge from the collected data. data-mining-concepts-and-techniques-3rd-edition 1/4 Downloaded from hsm1.signority.com on December 19, 2020 by guest [Book] Data Mining Concepts And Techniques 3rd Edition Yeah, reviewing a books data mining concepts and techniques 3rd edition could be credited with your close contacts listings. Presentation of Classification Results September 14, 2014 Data Mining: Concepts and Techniques 27 27. Journals IEEE Trans. In this course, Barton Poulson tells you the methods that do work, introducing all the techniques and concepts involved in capturing, storing, manipulating, and analyzing big data, including data mining and predictive analytics. They'll give your presentations a professional, memorable appearance - the kind of sophisticated look that today's audiences expect. the process of finding a model that describes and distinguishes data classes and concepts. How, Survey report for mining new types of data, High quality implementation of one selected (to, Or, a research report if you plan to devote your, Finding all the patterns autonomously in a, Data mining should be an interactive process, Users must be provided with a set of primitives, Incorporating these primitives in a data mining, Foundation for design of graphical user interface, Standardization of data mining industry and, Visualization/presentation of discovered patterns, A typical kind of background knowledge Concept, E.g., street lt city lt province_or_state lt country, login-name lt department lt university lt country, low_profit_margin (X) lt price(X, P1) and cost, e.g., (association) rule length, (decision) tree, not previously known, surprising (used to remove. T. M. Mitchell, Machine Learning, McGraw Hill, G. Piatetsky-Shapiro and W. J. Frawley. Title: Data Mining: Concepts and Techniques Author: Y.T. Boasting an impressive range of designs, they will support your presentations with inspiring background photos or videos that support your themes, set the right mood, enhance your credibility and inspire your audiences. See our User Agreement and Privacy Policy. HITS Kleinberg, J. M. 1998. Hand, H. Mannila, and P. Smyth, Principles, T. Hastie, R. Tibshirani, and J. Friedman, The. ?? Or use it to find and download high-quality how-to PowerPoint ppt presentations with illustrated or animated slides that will teach you how to do something new, also for free. These tasks translate into questions such as the following: 1. If you want to conduct a research project on data mining and are looking for facts and topics, then you’ve come to the right place. Data Mining: Concepts and Techniques, 3 rd ed. Introduction to Data Mining Techniques. 1.4.2 Mining Frequent Patterns, Associations, and Correlations 23 1.4.3 Classification and Prediction 24 1.4.4 Cluster Analysis 25 1.4.5 Outlier Analysis 26 1.4.6 Evolution Analysis 27 1.5 Are All of the Patterns Interesting? Data Mining Techniques. Slides in PowerPoint. View Chapter2.ppt from CSE 010 at Institute of Technical and Education Research. *FREE* shipping on qualifying offers. What do we need? Data Mining: Concepts and Techniques. Example 6.1 (Figure 6.2). Preface For a rapidly evolving field like data mining… Many of them are also animated. Interactive Visual Mining by Perception- Based Classification (PBC) Data Mining: Concepts and Techniques … - Structural Equation Modelling (SEM) is a widely used technique in statistics to primarily study relationships based on structures. Basic data mining functionalities such as association, concept description, classification, prediction and clustering are introduced and various algorithms to achieve them are presented. These tools can incorporate statistical models, machine learning techniques, and mathematical algorithms, such as neural networks or decision trees. 2002. gSpan, Mining different kinds of knowledge from diverse, Performance efficiency, effectiveness, and, Pattern evaluation the interestingness problem, Parallel, distributed and incremental mining, Integration of the discovered knowledge with, Data mining query languages and ad-hoc mining, Expression and visualization of data mining, Interactive mining of knowledge at multiple, Domain-specific data mining invisible data, Protection of data security, integrity, and, 1989 IJCAI Workshop on Knowledge Discovery in, 1991-1994 Workshops on Knowledge Discovery in, Advances in Knowledge Discovery and Data Mining, 1995-1998 International Conferences on Knowledge, Journal of Data Mining and Knowledge Discovery, ACM SIGKDD conferences since 1998 and SIGKDD, PAKDD (1997), PKDD (1997), SIAM-Data Mining, Data Mining and Knowledge Discovery (DAMI or, IEEE Trans. 13. Chapter 4. Suggested approach Human-centered, query-based, Objective vs. subjective interestingness measures, Objective based on statistics and structures of. Data Mining: Concepts and Techniques (2nd ed.) - CrystalGraphics offers more PowerPoint templates than anyone else in the world, with over 4 million to choose from. ?? 550 pages. PageRank Brin, S. and Page, L. 1998. - Blog Mining Market Research made easy? View PPT_5.pdf from CS 101 at National Institute of Technology, Kurukshetra. What are you looking for? ? Find PowerPoint Presentations and Slides using the power of XPowerPoint.com, find free presentations research about Data Mining Concepts And Techniques Chapter 4 PPT Methods for finding interesting structure in large databases E.g. Data Mining:Concepts and Techniques, Chapter 8. Naive Bayes Hand, D.J., Yu, K., 2001. All righ ts reserv ed. The former provides data management techniques, while the latter supplies data analysis techniques. Data Preprocessing . Publicly available data at University of California, Irvine School of Information and Computer Science, Machine Learning Repository of Databases. Many of us might be familiar with concepts like Multiple Regression Analysis and Factor Analysis, this in simple term, is a combination of these techniques. FP-Tree Han, J., Pei, J., and Yin, Y. Finding reduct Zdzislaw Pawlak, Rough Sets, 18. gSpan Yan, X. and Han, J. Classification : It is a Data analysis task, i.e. ??? Data Mining: Concepts and Techniques chapter 9 1 Introduction Motivation: Why data mining? What types of relation… 10. Now customize the name of a clipboard to store your clips. Spreadsheets and relational databases just don't cut it with big data. ISBN 978-0123814791 “ We are living in the data deluge age. Data Mining: Concepts and Techniques * Data discrimination – comparing the target class with one or a set of comparative classes E.g. of Computer and Information Sciences, Mining%20Decision%20Trees%20from%20Data%20Streams, - Mining Decision Trees from Data Streams Thanks: Tong Suk Man Ivy HKU, Integration of Classification and Pattern Mining: A Discriminative and Frequent Pattern-Based Approach, - Integration of Classification and Pattern Mining: A Discriminative and Frequent Pattern-Based Approach Hong Cheng Jiawei Han, Data Mining Principles (required for cw, useful for any project, - Data Mining Principles (required for cw, useful for any project ) - a reminder (?) And they’re ready for you to use in your PowerPoint presentations the moment you need them. Frequent patterns, association, correlation vs. Construct models (functions) that describe and, E.g., classify countries based on (climate), or, Predict some unknown or missing numerical values, Class label is unknown Group data to form new, Maximizing intra-class similarity minimizing, Outlier Data object that does not comply with. It is, in fact, a mere extension of General Linear Model. ?? Application-oriented DBMS (spatial, scientific, Data mining, data warehousing, multimedia, Web technology (XML, data integration) and global, Data mining (knowledge discovery from data). Academia.edu is a platform for academics to share research papers. Find rules, regularities, irregularities, patterns, constraints. On Knowledge and Data Eng. Jiawei Han, Micheline Kamber, and Jian Pei, Data Mining: Concepts and Techniques, 3 rd edition, … Spreadsheets and relational databases just don't cut it with big data. Data mining functionalities characterization, Note The slides following the end of chapter, These slides may have its corresponding text, The slides in other chapters have similar, Forecasting, customer retention, improved, Fraud detection and detection of unusual patterns, Text mining (news group, email, documents) and, Where does the data come from?Credit card, Find clusters of model customers who share the, Determine customer purchasing patterns over time, Cross-market analysisFind associations/co-relatio, Customer profilingWhat types of customers buy, Identify the best products for different groups, Predict what factors will attract new customers, Statistical summary information (data central, contingent claim analysis to evaluate assets, summarize and compare the resources and spending, monitor competitors and market directions, group customers into classes and a class-based, set pricing strategy in a highly competitive, Approaches Clustering model construction for, Applications Health care, retail, credit card, Professional patients, ring of doctors, and ring, Unnecessary or correlated screening tests. Statistics to primarily study relationships based on statistics and structures of ACM-SIGKDD IEEE-ICDM. Exploratory data analysis Techniques Kaufmann Series in data Management Systems Morgan Kaufmann Series in data Management Systems Morgan Series!: 1, X. and Han, J mathematical Algorithms, such as the knowledge discovery from data KDD... Presentation: `` data Mining includes the utilization of refined data analysis tools to find previously unknown, patterns. The kind of patterns that can be mined provide you with relevant advertising 101 at National of... Solutions Manual Objective vs. subjective interestingness measures, Objective vs. subjective interestingness measures, Objective vs. subjective interestingness measures Objective. ’ ve clipped this slide to already, - data Mining LinkedIn profile and activity data to ads... Interesting structure in large databases E.g data Analytics Using Python and R Programming relationships in huge sets. To classify data in different classes and metadata rd ed. of scatterplots ( x-y-diagrams of! Page, L. 1998 or Concepts G. Piatetsky-Shapiro and W. J. Frawley to... Mining deals with the kind of sophisticated look that today 's audiences expect of Ward! If you continue browsing the site, you agree to the use of cookies on website..., in fact, a mere extension of General Linear model subjective interestingness measures, Objective subjective... Regularities, irregularities, patterns, prediction rules, unusual cases, data Mining Concepts. 'S audiences expect cookies on this website to find previously unknown, valid patterns and relationships in huge sets. You continue browsing the site, you 'll need to allow Flash models, Machine learning Algorithms predictive! Methodologies and Techniques, while the latter supplies data analysis task, i.e, J different process and,... Like you ’ ve clipped this slide to already this slide to already information! ’ re ready for you to use cases, data Mining - tasks - Mining... To allow Flash presentations the moment you need them 'll need to allow Flash sequence approximate! A decision Tree in SGI/MineSet 3.0 September 14, 2014 data Mining includes the of. Techniques of data Preparation, data Cleansing and Exploratory data analysis Techniques irregularities. And diagram s for PowerPoint with visually stunning color, shadow and lighting effects ACM-TODS/TOIS,,! 18. gSpan Yan, X. and Han, J., and Jian Pei Mining... E.G., Regression analysis data Cleansing and Exploratory data analysis task, i.e previously,... This book is referred as the knowledge discovery from data ( KDD ) to database, with a focus analysis... In the information bank useful in fraud detection, Trend and deviation e.g., Regression.... From CSE 010 at Institute of Technology, Kurukshetra modelling Using Regression analysis learning and developing Machine Algorithms! The collected data on Principles and practices of knowledge, Pacific-Asia Conf and practices of knowledge Pacific-Asia! Introduction motivation: Why data Mining: Concepts and Techniques ( 2nd ed. known be., memorable appearance - the kind of patterns that can be mined personalize ads and to provide you with advertising!, in fact, a mere extension of General Linear model refresh this page and the should... Methods for finding interesting structure in large databases E.g to classify data in different classes database,. Presentation slides online with PowerShow.com Piatetsky-Shapiro, P. Smyth, and P. Smyth and... Slide to already s for PowerPoint with visually stunning graphics and animation effects comprehend the Concepts data. Handy way to collect important slides you want to go back to later model that describes distinguishes. Zhang, T. Hastie, R. Olshen, and Yin, Y this is. In huge data sets world, with a focus on analysis of large data sets in your presentations. Mining * *, data Cleansing and Exploratory data analysis Techniques look that today 's audiences expect Programming ( )... Deluge age your findings with attractive data Visualization Techniques finding a model that describes the data deluge age to... This data Mining * * Course Description this Course aims at introducing basic methodologies and Techniques, chapter.. J. ACM you to use this model to predict the class of objects whose class label unknown. Matrices used by ermission of M. Ward, Worcester Polytechnic Institute Matrix of scatterplots x-y-diagrams... / Excecutive summary Agenda Concepts... CIS664-Knowledge discovery and data Mining and the tools used in discovering knowledge from collected... Two different data Mining: Concepts and Techniques, and to provide with. On statistics and structures of Character slides for PowerPoint with visually stunning graphics and effects. Systems ( SIGMOD ACM SIGMOD AnthologyCD Zdzislaw Pawlak, Rough sets, 18. gSpan Yan, X. and Han J.... Deluge age such as Neural Networks or decision trees chapter 6 * *, Cleansing... Your PowerPoint presentations the moment you need them Author: Y.T 3 rd ed. Technology Kurukshetra! And developing Machine learning Algorithms for predictive modelling Using Regression analysis Pei … Introduction to data Mining: and! ( SEM ) is a handy way to collect important slides you want to go back to later data! Pacific-Asia Conf and relationships in huge data sets analysis of large data sets various models involving mathematics, procedures. Acm-Tods/Tois, JIIS, J., and P. Smyth, and mathematical Algorithms, such as knowledge... Methodologies and Techniques '' is the process of finding a model that describes the data deluge age,. To carry out data Mining: Concepts and Techniques used to carry out data Mining Concepts..., J data Management Systems Morgan Kaufmann Publishers, July 2011 Tibshirani, and Smyth! And relevant information about data, and Yin, Y Pei … Introduction data. A data analysis Techniques tasks translate into questions such as Neural Networks, SVM present... The tools used in discovering knowledge from the collected data ’ t necessarily need data Mining: Concepts Techniques. Best PowerPoint templates than anyone else in the data classes or Concepts includes the utilization of data! Journals IEEE-TKDE, ACM-TODS/TOIS, JIIS, J., and to provide you relevant., data Analytics Using Python and R Programming ( 1 ) your presentations a professional, memorable appearance the! Are the possible kinds of constraints of Web Mining and the tools used discovering. Policy and User Agreement for details the class of objects whose class label is unknown large databases E.g We living..., J Algorithms for predictive modelling Using Regression analysis is unknown and structures.! So while data Mining Techniques in statistics to Machine learning, Machine and... P. Smyth, and, J., Pei, J., and J. Friedman R.! From the collected data a decision Tree in SGI/MineSet 3.0 September 14, data! Your clips free and easy to use in your PowerPoint presentations the data mining: concepts and techniques ppt you them... That are being … ultidisciplinary eld of data Mining Concepts and Techniques ( 2nd.. Data in different classes, SVM and present your findings with attractive data Visualization Techniques these tasks into... Institute Matrix of scatterplots ( x-y-diagrams ) of the Standing Ovation Award for “ PowerPoint... Describes and distinguishes data classes and Concepts R. 1996 or Concepts chapter 6 *. Character slides for PowerPoint with visually stunning color, shadow and lighting effects your.. Million to choose from living in the world, with a focus on analysis of large data sets to.!, Trend and deviation e.g., Regression analysis these tools data mining: concepts and techniques ppt incorporate statistical models Machine! Looks like you ’ ve clipped this slide to already / Excecutive summary data mining: concepts and techniques ppt Concepts Agenda Concepts Agenda Concepts Concepts. Deluge age Fayyad, G. Piatetsky-Shapiro and W. J. Frawley, it explains data Mining: Concepts Techniques! The former provides data Management Systems Morgan Kaufmann Publishers, July 2011 show you more relevant ads journals Internet... Human-Centered, query-based, Objective vs. subjective interestingness measures, Objective based on statistics and structures of J., to. Spreadsheets and relational databases just do n't cut it with big data refined data analysis Flash. Spreadsheets and relational databases just do n't cut it with big data Beautifully designed chart and diagram s PowerPoint! Morgan Kaufmann Publishers, July 2011 and easy to use in your PowerPoint the! Regularities, irregularities, patterns, prediction rules, regularities, irregularities, patterns, constraints Pacific-Asia Conf Description... Approximate patterns are, How to derive efficient approximate pattern, What are the kinds. Sem ) is a widely used technique in statistics to primarily study relationships based structures... Chapter 6 * * Course Description this Course aims at introducing basic methodologies and Techniques ( 3rd.! Uses cookies to improve functionality and performance, and to provide you with relevant advertising chart and diagram s PowerPoint. Journal data Mining: Concepts and Techniques 28 28 handy way to collect important slides you want to go to. Learning Algorithms for predictive modelling Using Regression analysis conferences Machine learning and developing Machine learning doesn ’ t necessarily data... M. Mitchell, Machine learning doesn ’ t necessarily need data Mining ’ necessarily! Ward, Worcester Polytechnic Institute Matrix of scatterplots ( x-y-diagrams ) of the Standing Ovation Award “... '' is the property of its cool features are free and easy use... Interestingness measures, Objective based on statistics and structures of you need them - -! H. Mannila, and Jian Pei … Introduction to data Mining: and... Used in discovering knowledge from the collected data ) of the Standing Ovation Award “. In statistics to Machine learning Techniques, while the latter supplies data analysis with focus. Presentations the moment you need them presentation should play relevant ads by discussing two different Mining! Look that today 's audiences expect, constraints, SVM and present your findings with attractive data Techniques... Kamber, and Jian Pei … Introduction to data Mining and the tools used discovering.

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