1. TimelyBid.com Provide an integration between eBay and Google Calendar for quick and easy visualization of timely data regarding eBay bids. By Katie Varland, Josh Smith, Sean Humpherys MIS-510B with thanks to Dr. Chen & Xin Li

3. customer Timelybid.com Data miner with DM computer Spider & MySQL DB Dynamic reports Timely Bid Organization Registers API calls Flash MX Spider Update AI models Analyze & DM

4. Novelty IDEA  Integrate bid data into Google Calendar from eBay real time DATA MINING AWOL risk assessment using three distinct AI algorithms VISUALIZATION  Improved visualization of eBay data  Dynamic flash-based charts  Visualization of data mining predictions LEVERAGE OPEN SOURCE  Joomla & Joomla CMS modules  YALE/WEKA for data mining  XML/SWF Charts for dynamic charts

6. Open Source and Other Tools Joomla CMS  Customized user registration module  Available Virtuemart for Pay Pal integration $39.95 Apache/Linux/Php/MySQL eBay API Google Calendar API RapidMinger (YALE) / Weka for data mining XML/SWF Charts for dynamic charts (limited version free or full license $45)

8. Demo RapidMiner RapidMiner formerly YALE www.rapidminer.com  Download the OWN-free version for easy off-line mining  Download GPL version if you desire to dynamically link the system into your program

9. Business Model Provide an integration between eBay and Google Calendar for quick and easy visualization of timely data regarding eBay bids. Subscription model $12 / year Advertising model Uses Pay Pal as payment facilitator, integrates with Joomla’s user registration module

10. Production Costs Rent production server GoDaddy$ 6,000 /yr Rent development server GoDaddy$ 6,000 /yr Data mining computer$ 3,000 to buy Internet access$ 600 /yr Advertising Sales & Support staff$ 40,000/yr Development & data mining staff$ 50,000/yr Licensing and other costs$ 5000/yr Total$110,600 /yr

11. ROI Plan A: Slow growth by Owners  Break even after 1050 customers (not including advertising revenue) Plan B: Fast growth with investors  Break even after 9000 customers (not including advertising revenue)

12. AI Avatars for AWAL Risk Assessment AI Avatar Joseph is our risk adverse assessor using C4.5 AI Avatar Julie is an moderate risk assessor using AD Tree algorithm AI Avatar Scott is our risk seeking assessor using REP Tree.

13. Data Mined Data collected from eBay for mining purposes isRegistered as dependent variable userID Lifetime Positive Feed Back% Feed Back Score All Positive FB Member Since Location # Items for Sale # of SubCategories # of Main Categories # of One Month Positive Feedback # of Six Months Positive FB # of Twelve Months Positive FB # of One Month Negative FB # of Six Months Negative FB # of Twelve Months Negative FB # of Positive FB # of Negative FB # FB Withdrawn# Bids Retracted

14. Code for Avatars if($userArray['twelveMoNeg'] < 1.5) { if ($userArray['twelveMoPos'] < 0.5) { if ($userArray['numPosFB'] < 46.5) {$vote = true;} else if ($userArray['numPosFB'] >= 46.5) { if($userArray['posFB'] < 97.55) {$vote = false;} else if($userArray['posFB'] >= 97.55) { if ($userArray['allPosFB'] < 23450.5) { if ($userArray['allPosFB'] < 13578.5) {$vote = false;} else if ($userArray['allPosFB'] >= 13578.5) {$vote = true;} } else if ($userArray['allPosFB'] >= 23450.5) {$vote = false;} } else if ($userArray['twelveMoPos'] >= 0.5)

15. AWOL Risk Assessment Collected nearly 150,000 records on eBay users In experimental phase, used up to 80,000 records for training. Resulted in over- learning but identified important attributes. In production phase, used 13,000 specially selected records to train and 50,000 to test. Achieved between 95% and 98% accuracies on predicting if the user became unregistered in the last thirty days.

16. How to Chart Data XML/SWF Charts Charts.swf PHP Demo

17. Responsibilities Josh  Google API  Integrating everything together  User Registration Katie  eBay API  Spiders  Data mining collection Sean  TimelyBid website  Data mining algorithms  Database