1. Cases on Association Rules: Association Rules Graphs and Cases

2. Association Rules and Graphic Representation of Relationships Among Items

3. A store selling vegetables and fruits

4. I. POS Data (1000 data) bananas plums, lettuce, tomatoes celery, bean bean apples, carrots, tomatoes, potatoes potatoes bean carrots bean apples, oranges, lettuce, tomatoes peaches, oranges, celery, potatoes, bean beans oranges, lettuce, carrots, tomatoes apples, bananas, plums, carrots, tomatoes, onions, bean apples, potatoes lettuce, peas, beans.

5. 2. Association Rules as Output (Model) Only 55 rules satisfy the specified constraints. tomatoes -> lettuce [Coverage=0.263 (263); Support=0.111 (111); Strength=0.422; Lift=1.94; Leverage=0.0539 (53.9); p=2.35E-019] lettuce -> tomatoes [Coverage=0.217 (217); Support=0.111 (111); Strength=0.512; Lift=1.94; Leverage=0.0539 (53.9); p=2.35E-019] tomatoes -> carrots [Coverage=0.263 (263); Support=0.085 (85); Strength=0.323; Lift=1.85; Leverage=0.0390 (39.0); p=1.83E-012] carrots -> tomatoes [Coverage=0.175 (175); Support=0.085 (85); Strength=0.486; Lift=1.85; Leverage=0.0390 (39.0); p=1.83E-012].

6. 3. Graphic Representation

7. Relationship graph when the link is set to 0

8. 링크의 강도를 6 으로 설정했을 경우의 그래프 Relationship graph when the distance is set by value - network form

9. When the link is set to 6 (network form)

10. Cases on Association Rules

11. CASE 1: Ice-cream -Target Brands & Variables

12. 1.Ice-cream -Target Brands & Variables Brands Gusttimo Baskin Robbins Natture Haagen-dazs Etc. Brands Varaibles Taste Price Mood Distance Brand Image Service Rumor Variables

13. Why do you visit there? ①.Taste ②.Price ③.Mood ④.Distance ⑤. Image ⑥. Service ⑦. Rumor 2.Questionnaires Where do you visit the most for ice cream? ①.Gusttimo ②.Baskin Robbins ③.Natture ④.Haagen-daz ⑤. Red Mango ⑥. Palazzo ⑦.etc

14. Choose the number below according to your value level when you choose to eat ice cream 3.Questionnaire Method Classification Not important-------------Most important Taste (1) (2) (3) (4) (5) (6) (7) Price (1) (2) (3) (4) (5) (6) (7) Mood (1) (2) (3) (4) (5) (6) (7) Distance (1) (2) (3) (4) (5) (6) (7) Image (1) (2) (3) (4) (5) (6) (7) Service (1) (2) (3) (4) (5) (6) (7) Rumor (1) (2) (3) (4) (5) (6) (7)

15. 4.Average value on each variables

16. 5.Derive rules by using Magnum Opus Mood -> Red Mango [Coverage=0.025 (4); Support=0.019 (3); Strength=0.750; Lift=4.11; Leverage=0.0143 (2.3); p=0.0195] Red Mango -> Mood [Coverage=0.182 (29); Support=0.019 (3); Strength=0.103; Lift=4.11; Leverage=0.0143 (2.3); p=0.0195] Baskin -> distance [Coverage=0.390 (62); Support=0.145 (23); Strength=0.371; Lift=2.03; Leverage=0.0735 (11.7); p=1.28E-006] distance -> Baskin [Coverage=0.182 (29); Support=0.145 (23); Strength=0.793; Lift=2.03; Leverage=0.0735 (11.7); p=1.28E-006] Gustimo -> Taste [Coverage=0.258 (41); Support=0.233 (37); Strength=0.902; Lift=1.56; Leverage=0.0835 (13.3); p=3.18E-007] Taste -> Gustimo [Coverage=0.579 (92); Support=0.233 (37); Strength=0.402; Lift=1.56; Leverage=0.0835 (13.3); p=3.18E-007]

17. CASE 2: Lotte World

18. Contents1 1.Problem Definition & constraints 2.Phases 3.Alternatives 1. Using RFID 2. Exit Poll 4. Result Example 5. Effectiveness & application

19. Problem Definition & Phases2 Problem Definition - Attraction locating : avoid conflict between target segments - inefficient customer route  Lower customer satisfaction Constraints - Attraction re-location : Impossible 1. Data Mining 2. Using Model 3. Finding efficient customer route & Promotion strategy 4. Max (Customer satisfaction) Phases

20. HOW – Association Rules3 Association Rules Indicating & Choice of Alternatives 1. Using RFID - Clear understanding about customer’s moving route, location, time - Technical Difficulty, and Heavy cost 2. Exit Poll - Easy application - Light cost - Limit in data : quantity, quality Survey : Let customers to check all facilities they rode Make Market-Basket Association Rules Analysis : based on Market-Basket

21. Survey Example4 For Lotteworld AdventureFor Magic Island Adventure of Sinbad( )Atlantis( ) Spain Pirate Ship( )Gyro Drop( ) Frog Hooper( )Gyro Swing( ) Marry-go-round( )Bunge Drop( ) Crazy Bumper Car( )Comet Express( ) Kids Bumper car( )Marry-go-Round 3( ) Ball Battle( )Sky Surfing( ) Flume Ride( )Bumper car( ) Giant Roop( )Ghost House( ) Marry-go-round 2( )Castle Music Show( ) Illusion Odyssey( )Fantasy Dream( ) Out-Law( )Automoblile Racing( ) 4D Movies( )Kingdom of Children( ) Magic Theater( )EureKa( ) Puppet Theater( )Geneve Excursion Ship( ) French Revolution( )Lake Boat( ) Jungle Adventure( ) World Monorail( ) Rage of Parao( ) Balloon Travel( ) dynamic Theater( ) Animal Theater( ) Garden Stage Concert( ) Street Concert( ) Parade( ) ※ Mark Attractions that you rode today Basic information 1.gender 2.age 3.Marriage 4.Children 5.Age of Children 6.Place of Residence 7.others

22. Result Example & Applications5 1. Student (age 12~18) - P(Gyro drop  Atlantis) : 70% 2. Parents with Little children - P(Marry-go-Round  Kids Bumpercar) : 60% We will be able to check : Who is using what kind of facilities Finding Effective Route Making Promotion Strategy Locate extra store at specific customer’s route Result Example Applications

23. CASE 3: Gmart case

24. Data Collection : Gmart located at Yongsan - Customer data POS data from daily transaction - Location Chung-pa dong, Yongsa,, Seoul - Period 2005. 9. 1 ~ 2005. 12. 7. - Number of data 1,334 cases - Contents in the data POS fields names(date, time, POS manager, receipt number, product name, quantity, amount, classification) - G mart system screen -

25. Data Cookies, Milk Yogurt,Frozen fool Bear, Cookies,Coffee Milk, Water.

26. Extracted Association Rule Water -> Cookies Water -> Coffee and Newspaper

27. What is it?

28. Social Network (http ://nexus.ludios.net/view/demo)

29. Demo site http://hci.stanford.edu/jheer/projects/vizster/