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Series: Data Mining

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Fundamentals and latest developments

TALKS IN THIS SERIES (8)

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Play '1. Understanding business time-to-event problems using survival data mining (40 mins)'
1. Understanding business time-to-event problems using survival data mining (40 mins) More info
Mr. Gordon S. Linoff  –  Founder and Principal, Data Miners Inc., USA

TOPICS COVERED IN THIS TALK

  • Background on survival analysis from a data miner's perspective
  • Introduction to key ideas in survival analysis: hazards, survival, competing risks
  • Understanding survival and hazard charts
  • Quantifying loyalty marketing program
  • Voluntary and involuntary churn
  • Forecasting
Play '2. Data preparation (56 mins)'
2. Data preparation (56 mins) More info
Mr. Dorian Pyle  –  Director of Modeling, Numetrics Management Systems, USA

TOPICS COVERED IN THIS TALK

  • Why prepare data?
  • Six foundations for data preparation and modeling
  • Applicability of general data preparation techniques
  • What is data preparation?
  • Ideal data
  • Selecting data for modeling
  • Tools
  • Techniques
  • Introducing information transmission
  • Where to represent complexity?
  • Information transmission by mode
  • Signal and noise
  • Practical results
Play '3. Data mining algorithms - Part I (48 mins)'
3. Data mining algorithms - Part I (48 mins) More info
Prof. Ian Witten  –  Professor of Computer Science, University of Waikato, New Zealand

TOPICS COVERED IN THIS TALK

  • Simplicity first
  • One attribute does all the work
  • Complications: missing values
  • Overfitting
  • Evaluating the result
  • Description of the method
  • Statistical modeling
  • Bayes's rule
  • Weather data: probabilities
  • Zero frequencies, missing values
  • Numeric attributes
  • "Naive" statistical model
  • Constructing decision trees
  • Continuing to split
  • Highly-branching attributes
  • Overfitting and the need to prune
  • Constructing rules
  • Rules versus trees
  • General algorithm
  • Association rules
Play '4. Data mining algorithms - Part II (48 mins)'
4. Data mining algorithms - Part II (48 mins) More info
Prof. Ian Witten  –  Professor of Computer Science, University of Waikato, New Zealand

TOPICS COVERED IN THIS TALK

  • Linear models
  • Classification by regression
  • Support vector machine
  • Multilayer perceptron
  • Trees for numeric prediction
  • Instance based learning and clustering
  • Hierarchical clustering
  • Iterative: fixed num of clusters
  • Probabilistic clustering
  • Using and extending the mixture model
  • Bayesian clustering
  • Engineering the input and output
  • Attribute selection
  • Data transformations
  • Principal component analysis
  • Combining multiple models
  • Bagging
  • Randomization
  • Boosting
  • Stacking
  • Using unlabeled data
  • Co-training
Play '5. Data mining for Customer Relationship Management (61 mins)'
5. Data mining for Customer Relationship Management (61 mins) More info
Mr. Michael J. A. Berry  –  Founder, Data Miners Inc., USA

TOPICS COVERED IN THIS TALK

  • Businesses should establish a learning relationship with their customers
  • Data mining is a key enabler of the learning relationship
  • Business processes are organized around the customer relationship
  • Business processes generate data that can be used for modeling
  • Product penetration
  • Campaign response
  • Campaign profitability
  • Differential response analysis
  • Customer value
  • Recommendation and cross-selling
  • Forecasting remaining customer lifetime
Play '6. Overview of web mining and its applications - Part I (40 mins)'
6. Overview of web mining and its applications - Part I (40 mins) More info
Prof. Bamshad Mobasher  –  Professor of Computing, DePaul University, USA

TOPICS COVERED IN THIS TALK

  • Data mining
  • Knowledge discovery in data viewed as a process
  • Web content mining
  • Web usage mining
  • Web structure mining
  • Web content mining
  • Web content mining
  • Data preparation and representation
  • Approaches and application
  • Clustered search results
  • Personalized content delivery
  • Web structure mining
  • Google's PageRank algorithm
  • Hubs and authorities
  • Web communities
Play '7. Overview of web mining and its applications - Part II (39 mins)'
7. Overview of web mining and its applications - Part II (39 mins) More info
Prof. Bamshad Mobasher  –  Professor of Computing, DePaul University, USA

TOPICS COVERED IN THIS TALK

  • Web usage mining for e-business analytics
  • Typical sources of data and user transactions
  • A typical server log
  • Usage data preparation tasks
  • Levels of aggregation in web usage analysis
  • Conceptual representation of user transactions
  • Web usage mining as a process
  • Common tasks
  • Association analysis for e-commerce
  • Association rules
  • Characterizing user segments via clustering
  • Clustering user transactions
  • Collaborative filtering
  • Web personalization
Play '8. The past and future of data mining: where are we coming from, where are we going to? (42 mins)'
8. The past and future of data mining: where are we coming from, where are we going to? (42 mins) More info
Prof. Geoff Webb  –  Research Professor, Monash University, Australia

TOPICS COVERED IN THIS TALK

  • What is data mining?
  • The CRISP-DM model
  • Convergence of contributing disciplines
  • Commercial systems and methodologies
  • Business process analysis
  • Scientific data analysis
  • Text mining
  • Evolution of data centric businesses
  • Text mining
  • Evolution of data centric businesses
  • Privacy
  • Formalization and theory
  • Modeling high dimensional data
  • Verticals
  • CPU and data growth
  • Industry growth and specialization
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ABOUT THIS SERIES

Editor(s)

Mr. Tom Breur Show Biography

EDITOR BIOGRAPHY

Mr. Tom Breur – XLNT Consulting, The Netherlands

Tom has an academic background in psychology. Initially he majored in clinical psychology (1986), and later he went back to college to study economic psychology (1996) with an emphasis on quantitative methods. As a professional he has worked in database management, at the outset mainly from the ‘technical’ angle. Later he moved to exploiting information in databases, and combining database analysis with market research. Tom has held positions in non-profit and profit industry (financial services). While working at ING, among others, Tom managed the research department of ING Bank for the Netherlands. In 2004 he launched his own company, XLNT Consulting.

Publication Date

June, 2008

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Play 'Creating leaner supply chains'
Creating leaner supply chains More info
Prof. Peter Hines

TOPICS COVERED IN THIS TALK

  • The lean business model
  • Extended Enterprise
  • Creating lean supply chains
  • Tiered supply structure
  • Numbers of suppliers
  • Asset specificity
  • Maximum buy strategy
  • Bilateral Design
  • Supplier innovation
  • Relationships
  • Supplier measurement
  • Category management
  • Supplier associations
  • The Toyota production system

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