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Agenda Overview – London, UK – October 29-30, 2014
DAY 1: Wednesday October 29, 2014
8.00am-9.30am Registration and Coffee
9.30am-10.30am
Opening Session:
Le Mariage Parfait - Combining Logit and Ensemble Modeling for Increased Customer Churn Detection
Dr. Geert Verstraeten, PhD,
Program Chair Predictive Analytics World London
10.30am-10.55am Coffee Break
10.55am-11.40am Case Study: Belgian government
Gotch’all! Advanced Network Analysis for Detecting Groups of Fraud
Véronique Van Vlasselaer, KULeuven
11.40am-11.45am Session Change for Combo Pass Holders
11.45am-12.30pm Internet of Things Meets Customer Intelligence
Phil Winters, CIAgenda
12.30pm-1.40pm Lunch Break
1.40pm-2.40pm
Keynote
The Improbability Principle: Why Coincidences, Miracles, and Rare Events Happen Every Day

Prof. Dr. David J. Hand, Imperial College, London
2.40pm-2.45pm Session Change for Combo Pass Holders
2.45pm-3.30pm Case Study: Tata Sky
How Analytics Boosted Cross Sell Ratios for One of India's Largest Cable TV Companies
Ajay Kelkar, Hansa Cequity
3.30pm-3.55pm Coffee Break
3.55pm-4.40pm Case Study Activision
Cheating Detection in Call of Duty
Arthur Von Eschen, Activision
4.40pm-4.45pm Session Change for Combo Pass Holders
4.45pm-5.45pm Predicting a Better World: Three Case Studies Using Data for Good
Duncan Ross, DataKind UK
5.45pm-7.00pm Networking Reception

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DAY 2: Thursday October 30, 2014
8.30am-9.30am Registration and Coffee
  Thought Leader
9.30am-10.30am
Keynote
The Peril of Vast Search
(and How Target Shuffling Can Save Science)

Dr. John Elder, Elder Research, Inc.
(Also see Dr. Elder's full-day workshop on Oct. 31)
10.30am-10.55am Coffee Break
10.55am-11.40am The Power of Simulating Buying Flows
Dieter Debels, Geo Intelligence
11.40am-11.45am Session Change for Combo Pass Holders
11.45am-12.30pm Case Study: Booking.com
User Engagement at Booking.com through Topic Modelling in Travel
Lukas Vermeer, Booking.com
12.30pm-1.40pm Lunch Break
1.40pm-2.40pm
Keynote
The Revolution in Retail Customer Intelligence

Dean Abbott, Abbott Analytics, Inc.
2.40pm-2.45pm Session Change for Combo Pass Holders
2.45pm-3.30pm Case Study: verivox.de
Use of Large Data Sets to Predict User Behavior and Optimize Marketing Spending
Gergely Kalmár, Webrepublic AG
3.30pm-3.55pm Coffee Break
3.55pm-4.40pm Case Study: NSA
Analytics to Detect Malicious Use of Internet Anonymizers

Dr. Aaron Ferguson, National Security Agency (NSA)
4.40pm-4.45pm Session Change for Combo Pass Holders
4.45pm-5.30pm Predicting the Future: The Data Mining Approach to Time-Series Analysis
Tom Khabaza, Society of Data Miners

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Post-Conference Workshop: Friday October 31, 2014
Full-day Workshop
The Best and the Worst of Predictive Analytics:
Predictive Modeling Methods and Common Data Mining Mistakes

Dr. John Elder, CEO and Founder,
Elder Research, Inc.

Register

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