Using Metadata to Improve Search User Interfaces

1. Using Metadata to Improve Search User Interfaces Marti Hearst UC Berkeley FLINT Workshop, August 2001

2. My Claims • Web Search is OK • Gets people to the right starting points • Web SITE search is NOT ok • The best way to improve site search is • NOT to make new fancy algorithms • Instead …

3. The best wasy to improve search: Improve the User Interface

4. Recent Study by Vividence Research • Spring 2001, 69 web sites • The most common problems: • 53% had poorly organized search results • 32% had poor information architecture • 32% had slow performance • 27% had cluttered home pages

5. Organizing Search Results • There is a lot of prior work on this • Cha-Cha (Chen et al. 1999) • Scatter-Gather clustering (Cutting et al. 93, Hearst et al. 1996) • Becoming more prevalent in web search too. • Teoma • Visimo • Northern Light

6. Putting Results into Categories

7. Usually doesn’t work well when drilling down, however

11. Web Search Results Grouping • Drill down one category • Cannot mix and match categories • Probably isn’t all that useful • But …what about site search?

12. A Taxonomy of WebSites high Complexity of Data low low high Complexity of Applications From Mecca et al., WebDB’99

13. An Important Trend • Web sites generated from databases • Implications: • Web sites can adapt to user actions • Web sites can be instrumented

14. Navigation on the Web • Web search engines are good at getting people to the right site. • But … what happens when the user reaches the site? Follow Links … or … Search

15. text search An Analogy hypertext

16. Goal: An All-Tertrain Vehicle • The best of both techniques • A vehicle that magically lays down track to suggest choices of where you want to go next based on what you’ve done so far and what you are trying to do • The tracks follow the lay of the land and go everywhere, but cross over the crevasses • The tracks allow you to back up easily

17. GeoRegion + Time/Date + Topic + Role New interfaces are mixing and matching thesaurus-style metadata The question: how to do this effectively?

18. Goals for Metadata Usage • Well-integrated with search • Provides useful hints of where to go next • Tailored to task as it develops • Personalized • Dynamic

19. The FLAMENCO Project FLexible Access using MEtadata in Novel Combinations • Main goal: • Perform systematic studies to determine how metadata should be incorporated into search • Answer questions such as: • Given a set of user goals and a set of information: • How many metadata combinations to show? • What level of detail to show? • How best to preview and postview choices?

20. Evaluation Methodology • Regression Test • Select a set of tasks • Use these throughout the evaluation • Start with a baseline system • Evaluate using the test tasks • Add a feature • Evaluation again • Compare to baseline • Only retain those changes that improve results

21. Recipe Example

22. soar.berkeley.edu/recipes

23. soar.berkeley.edu/recipes

24. soar.berkeley.edu/recipes

25. www.epicurious.com

26. www.epicurious.com

27. www.epicurious.com

28. www.epicurious.com

29. Epicurious Metadata Usage • Advantages • Creates combinations of metadata on the fly • Different metadata choices show the same information in different ways • Previews show how many recipes will result • Easy to back up • Supports several task types • ``Help me find a summer pasta,'' (ingredient type with event type), • ``How can I use an avocado in a salad?'' (ingredient type with dish type), • ``How can I bake sea-bass'' (preparation type and ingredient type)

30. Ingredient Dish Cuisine Prepare Recipe Metadata usage in Epicurious

31. Ingredient Dish Cuisine Prepare Select Dish Cuisine Prepare I Metadata usage in Epicurious

32. Ingredient Dish Cuisine Prepare > Dish Cuisine Prepare Group by Metadata usage in Epicurious I

33. Ingredient Dish Cuisine Prepare Dish Cuisine Prepare Group by Metadata usage in Epicurious > I

34. Ingredient Dish Cuisine Prepare Dish Cuisine Prepare Group by Metadata usage in Epicurious > I Select I Cuisine Prepare

35. Metadata Usage in Epicurious • Can choose category types in any order • But categories never more than one level deep • And can never use more than one instance of a category • Even though items may be assigned more than one of each category type • Items (recipes) are dead-ends • Don’t link to “more like this” • Not fully integrated with search

36. Epicurious Basic Search Lacks integration with metadata

38. The FLAMENCO PROJECTUsability Studies to determine how to improve website search Marti Hearst Rashmi Sinha Ame Elliott Jen English Kirsten Swearington Ping Yee http://bailando.sims.berkeley.edu/flamenco.html

39. The FLAMENCO Project • Usability studies to determine how to improve site search using metadata • Researchers: • Marti Hearst, Rashmi Sinha • Ame Elliott, Jennifer English, Kirstin Swearington, Ping Yee • So far: • Epicurious usability study • Image search interface framework and study design

40. Epicurious Usability Study • 9 participants so far • Independent Variables: • 1) Epicurious Interface (Basic vs. Enhanced vs. Browse) • 2) Task type (known-item search vs. browsing for inspiration) • 3) Degree of constraint of query • 4) Number of results required (1 vs. many) • Dependent Variables: • 1) Time to find satisfactory recipe(s) • 2) Navigation path (backtracking, starting over, revising queries) • 3) Satisfaction with results of search • 4) Satisfaction with individual system features (e.g. breadcrumbs, query previews, refine by hyperlinks) • 5) Likelihood of using each interface in the future.

41. Epicurious Usability Study • Participants were asked to: • Do 3 pre-specified searches in advance • In the lab: • Specify a cooking scenario of interest to them • Search for 3 recipes for this recipe • Search for each recipe using each of the interfaces • Complete several structured tasks • Along the way, answer questions about • Getting closer or farther away from goal • Satisfaction with search results • Satisfaction with the interace

42. Usability Study: Preliminary Results, Preference Data

43. Usability StudyPreliminary Results: Feature Preference

44. Usability StudyPreliminary Results: Quantitative

45. Usability StudyPreliminary Results: Constraint-based Preferences

46. Usability Study Results: Summary • People liked the browsing-style metadata-based search and found it helpful • People sometimes preferred the search-style metadata search when the task was more constrained • But zero results are frustrating • This can be alleviated with query previews • People disprefer the standard simple search

47. Application to Image Search

48. Image Search: What is the task? • Illustrate my slides? • “Find a crevasse” • Keyword match works pretty well • Find inspiration for an architectural design? • Needs richer search support

49. Faceted Metadata Image: Architect: Period: Location: Concept: Planalto Palace Parti Communiste Francais Pantheon Oscar Neimeyer Oscar Neimeyer Jacques-Gabriel Soufflot 20th Century 20th Century 17th & 18th C. Brasilia Paris Paris Stone Curvilinear Stone

50. Faceted Metadata Image: Architect: Period: Location: Concept: Planalto Palace Parti Communiste Francais Pantheon Oscar Neimeyer Oscar Neimeyer Jaques-Gabriel Soufflot 20th Century 20th Century 17th & 18th C. Brasilia Paris Paris Stone Curvilinear Stone