Ch. 8: Concepts and categories

1. Ch. 8: Concepts and categories

2. Concepts and categories • Pink is basically red. • 99 is almost 100. • Orange is sort of yellow. • Austin is like Rome. • San Antonio is very much like Mexico. • Pita can be bread.

3. Concepts and categories II • Red is basically pink. • 100 is almost 99. • Yellow is almost orange. • Rome is like Austin. • Mexico is very much like San Antonio. • Bread can be pita.

4. Furniture (chair, lamp, rug, dresser, desk, stove, table, stool, television, fan, bed, television, counter) • Fruit (apple, grapefruit, watermelon, banana, cherries, boysenberry, pear, strawberries, lemon, orange, pineapple, nut) • Vehicle (car, airplane, sled, bus, bicycle, wheelchair, truck, boat, tractor, ambulance, trolley, wagon). • Weapon (pistol, arrow, slingshot, sword, tomahawk, whip, knife, cannon, fist, rifle, club, bow) • Vegetable (peas, celery, mushrooms, corn, turnips, potatoes, carrots, tomatoes, green onions, green beans, artichoke, pumpkin)…. • Other categories, bird, sport, toy, clothing.

5. Results: • Correlations: 0.95 or up (=1 is perfect correlation) • People agree very much which items are good/bad examples of a particular category. • Categories have “good” examples and “bad” examples. • The boundaries of categories are graded, and may be arranged probabilistically with “goodness” of membership. • What determine “goodness”? Or what makes a particular item a good example of a category?

6. Which desk is the best example of “desk”?

7. Fruit vs. Vegetable Onion Carrot Pepper Potato Jalapeno Cucumber Bitter Melon Spinach Garlic Ginger Broccoli Plantain Lettuce Cabbage Pumpkin Banana Apple Melon Grapes Lemon Avocado Orange Grape fruit Kiwi Papaya Mango Lime Tomato

8. Example: • Fruits  banana • Sweet, can eat without cooking, lots of vitamin, from tropical countries, soft, ripe quickly, easy to eat, kids love it, tasty, can bring it for hiking • Vegetables  carrot • Not sweet, not tasty, require some cooking, lots of vitamin, from anywhere, hard, stay long, kids don’t like it, hard

9. Which woman looks more attractive/friendly/pleasant/capable?

10. + =

11. Prototypes • Representation

13. How do we classify? • Given a person, we say he is a “sexist!!” • Given a person, we say she is an “extrovert.” • Given a person, we say he is a “liberal.” • Given a person, we say she is “terrorist.” • How do we do this?

15. Examine how people classify • What do you do first?

16. What hypothesis do you want to test?

17. What do you mean by “similar”? • Define it. •  operationally define it?

19. Similarity  features? • Matching features?

21. Classification • Similarity • Matching features. • How do people classify things? • Look at matching features •  compare the number of matching features.

23. What kind of relationship do you predict?

24. Finding • People look at matching features for classification

25. Some problems: • How about just storing what you saw before? • Exemplar models • What are features? • Prototypes for ad hoc categories??

26. Prototypes • What are they?

27. Problem I: Exemplar models (alternative to prototype models) • The categories you form is a collection of specific instances you experienced. • E.g., “dog” is a collection of specific dogs you saw before.

28. Problem II: Ad hoc categories • People I adore, People I admire, People I hang around, People I need, People I avoid. • Things I love, Things I enjoy, Places I love, Food I hate, music I like, movies I enjoy • countries I want to visit, restaurants I avoid

29. Problem III: What are features? • How do we know that an object A has features a, b, c, d….. Is it so obvious?

32. Austria Sweden Poland Hungary Demonstration • Tell me which country is most similar to Austria?

33. Demonstration • Tell me which country is most similar to Austria (Tversky, 1977)? Austria Sweden Norway Hungary

34. Austria Norway Sweden Hungary Austria Sweden Poland Hungary Depending on how you group countries, you perceive different features