پاورپوینت کامل Data Mining: Concepts and Techniques 42 اسلاید در PowerPoint

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پاورپوینت کامل Data Mining: Concepts and Techniques 42 اسلاید در PowerPoint

اسلاید ۴: January 3, 2018پاورپوینت کامل Data Mining: Concepts and Techniques 42 اسلاید در PowerPoint4Where to Find the Set of SlidesTutorial sections (MS PowerPoint files):http://.ca/~han/dmbookOther conference presentation slides (.ppt):http://db.cs.sfu.ca/ or http://.ca/~hanResearch papers, DBMiner system, and other related information: http://db.cs.sfu.ca/ or http://.ca/~han

اسلاید ۵: January 3, 2018پاورپوینت کامل Data Mining: Concepts and Techniques 42 اسلاید در PowerPoint5Chapter 1. IntroductionMotivation: Why data miningWhat is data miningData Mining: On what kind of dataData mining functionalityAre all the patterns interestingClassification of data mining systemsMajor issues in data mining

اسلاید ۶: January 3, 2018پاورپوینت کامل Data Mining: Concepts and Techniques 42 اسلاید در PowerPoint6Motivation: “Necessity is the Mother of Invention”Data explosion problem Automated data collection tools and mature database technology lead to tremendous amounts of data stored in databases, data warehouses and other information repositories We are drowning in data, but starving for knowledge! Solution: Data warehousing and data miningData warehousing and on-line analytical processingExtraction of interesting knowledge (rules, regularities, patterns, constraints) from data in large databases

اسلاید ۷: January 3, 2018پاورپوینت کامل Data Mining: Concepts and Techniques 42 اسلاید در PowerPoint7Evolution of Database Technology (See Fig. 1.1)1960s:Data collection, database creation, IMS and network DBMS1970s: Relational data model, relational DBMS implementation1980s: RDBMS, advanced data models (extended-relational, OO, deductive, etc.) and application-oriented DBMS (spatial, scientific, engineering, etc.)1990s—۲۰۰۰s: Data mining and data warehousing, multimedia databases, and Web databases

اسلاید ۸: January 3, 2018پاورپوینت کامل Data Mining: Concepts and Techniques 42 اسلاید در PowerPoint8What Is Data MiningData mining (knowledge discovery in databases): Extraction of interesting (non-trivial, implicit, previously unknown and potentially useful) information or patterns from data in large databasesAlternative names and their “inside stories”: Data mining: a misnomerKnowledge discovery(mining) in databases (KDD), knowledge extraction, data/pattern analysis, data archeology, data dredging, information harvesting, business intelligence, etc.What is not data mining(Deductive) query processing. Expert systems or small ML/statistical programs

اسلاید ۹: January 3, 2018پاورپوینت کامل Data Mining: Concepts and Techniques 42 اسلاید در PowerPoint9Why Data Mining — Potential ApplicationsDatabase analysis and decision supportMarket analysis and managementtarget marketing, customer relation management, market basket analysis, cross selling, market segmentationRisk analysis and managementForecasting, customer retention, improved underwriting, quality control, competitive analysisFraud detection and managementOther ApplicationsText mining (news group, email, documents) and Web analysis.Intelligent query answering

اسلاید ۱۰: January 3, 2018پاورپوینت کامل Data Mining: Concepts and Techniques 42 اسلاید در PowerPoint10Market Analysis and Management (1)Where are the data sources for analysisCredit card transactions, loyalty cards, discount coupons, customer complaint calls, plus (public) lifestyle studiesTarget marketingFind clusters of “model” customers who share the same characteristics: interest, income level, spending habits, etc.Determine customer purchasing patterns over timeConversion of single to a joint bank account: marriage, etc.Cross-market analysisAssociations/co-relations between product salesPrediction based on the association information

اسلاید ۱۱: January 3, 2018پاورپوینت کامل Data Mining: Concepts and Techniques 42 اسلاید در PowerPoint11Market Analysis and Management (2)Customer profilingdata mining can tell you what types of customers buy what products (clustering or classification)Identifying customer requirementsidentifying the best products for different customersuse prediction to find what factors will attract new customersProvides summary informationvarious multidimensional summary reportsstatistical summary information (data central tendency and variation)

اسلاید ۱۲: January 3, 2018پاورپوینت کامل Data Mining: Concepts and Techniques 42 اسلاید در PowerPoint12Corporate Analysis and Risk ManagementFinance planning and asset evaluationcash flow analysis and predictioncontingent claim analysis to evaluate assets cross-sectional and time series analysis (financial-ratio, trend analysis, etc.)Resource planning:summarize and compare the resources and spendingCompetition:monitor competitors and market directions group customers into classes and a class-based pricing procedureset pricing strategy in a highly competitive market

اسلاید ۱۳: January 3, 2018پاورپوینت کامل Data Mining: Concepts and Techniques 42 اسلاید در PowerPoint13Fraud Detection and Management (1)Applicationswidely used in health care, retail, credit card services, telecommunications (phone card fraud), etc.Approachuse historical data to build models of fraudulent behavior and use data mining to help identify similar instancesExamplesauto insurance: detect a group of people who stage accidents to collect on insurancemoney laundering: detect suspicious money transactions (US Treasurys Financial Crimes Enforcement Network) medical insurance: detect professional patients and ring of doctors and ring of references

اسلاید ۱۴: January 3, 2018پاورپوینت کامل Data Mining: Concepts and Techniques 42 اسلاید در PowerPoint14Fraud Detection and Management (2)Detecting inappropriate medical treatmentAustralian Health Insurance Commission identifies that in many cases blanket screening tests were requested (save Australian $1m/yr).Detecting telephone fraudTelephone call model: destination of the call, duration, time of day or week. Analyze patterns that deviate from an expected norm.British Telecom identified discrete groups of callers with frequent intra-group calls, especially mobile phones, and broke a multimillion dollar fraud. RetailAnalysts estimate that 38% of retail shrink is due to dishonest employees.

اسلاید ۱۵: January 3, 2018پاورپوینت کامل Data Mining: Concepts and Techniques 42 اسلاید در PowerPoint15Other ApplicationsSportsIBM Advanced Scout analyzed NBA game statistics (shots blocked, assists, and fouls) to gain competitive advantage for New York Knicks and Miami HeatAstronomyJPL and the Palomar Observatory discovered 22 quasars with the help of data miningInternet Web Surf-AidIBM Surf-Aid applies