1. Context, Zones, and Usability Marti Hearst UC Berkeley Inktomi Seminar April 28, 2000

2. My Background Databases Natural Language Processing Human-Computer Interaction User Interfaces for Text Search

3. TileBars Scatter/Gather DynaCat Cat-a-Cone Search Interfaces: Past Projects Common Themes: Search Result Context Integrating Browsing & Search

4. Outline What are context zones? The importance of the task UI / HCI ideas & projects Workspaces Information previews Alternative UIs

5. HCI Well-designed interactive computer systems promote: Positive feelings of success, competence, and mastery. Allow users to concentrate on their work, rather than on the system.

6. WWW Context Zones Industry Intranet Desktop Cascading priority based on locality of information

7. WWW Context Zones IndustryIntranetDesktop Specific slice through the data: analyst vs salesperson, or legal vs. medical

8. WWW Context Zones IndustryIntranetDesktop Slice again based on task, e.g., research vs reporting

9. Why do this? General search is too broad Allows for customization of search space Eliminates irrelevant information in advance Reduces ambiguity of query word usage Uses the user’s background

10. Slicing by Topic Only Example: FindLaw A vertical slice through legal text

13. Slicing by Topic Only Is subject-specific search enough? Should better support different legal tasks Find prior art for patent infringement case Find weaknesses in the application of intellectual property law in the 6 th circuit court of appeals

14. Combining Collections News Business News Legal News Science News Science News Reports Patents Legal News Patents Law Schools What will users be using these for?

15. Cha-Cha Intranet Search (Chen, Hearst, Hong, & Lin 99)

17. The Importance of the Task Results from HCI suggest the importance of taking the task into account. Proving non-infringement (vs searching patent databases) Finding the denial-of-service hacker (vs browsing newsgroups) Anticipating the competition’s marketing strategies (vs getting all satellite news)

18. The Importance of the Task Example: Does download time matter? In one study, Spool found: (56kbit modem) Amazon: 36 sec/pg (avg) About.com: 8 sec/pg (avg) Users rated the sites: Fastest: Amazon Slowest: About.com Why?

19. The Importance of the Task Perceived speed Strong correlation between perceived speed and whether the users felt they completed their task Strong correlation between perceived speed and whether the users felt they always knew what to do next (scent).

20. How to incorporate the task? Workspaces Relevant information previews Task-sensitive question-answering Simplicity / Flexibility Tradeoff

21. Workspace The grouping together of sets of windows known to be functionally related to some activity or goal. (Bannon et al. 83)

22. Early Workspaces Xerox PARC Rooms (Hendersen & Card 86) Sun/HP X- windows task grouping Elastic Windows (Kandogan & Shneiderman 97) Task: General work context

23. Workspaces Restrict combinatons: Particular task type(s) Particular domain Relevant information collections Relevant operation types

24. The DLITE Workspace By Steve Cousins (Stanford PhD, now at PARC) Task-oriented workspace Specialized tools, collections, query forms A distributed information system Show network, remote server status Concurrently shareable across sites

25. DLITE (Cousins 97) Task: Technical research Sources: Bibliographic collection, WWW Operators: Summarize documents Translate documents Extract references Query form: Title, Author, Subject

26. Workspaces restrict the tools … … but there can still be too many items returned as the result of a search. Need to focus on the task in more detail.

27. Information Previews Give users a hint of what happens next Help users see and return to what happened previously Reduces mental work Recognition over recall Memory aid

28. Metadata-based Customization Time/DateTopicRoleGeoRegion 

29. Task-Specific Preview Combinations A Simple Example Yahoo restaurant guide combines: Region Topic (restaurants) + Attributes (cuisine) Related Information Other attributes (cuisines) Other topics related in place and time (movies)

30. Green: restaurants & attributes Red: related in place & time Yellow: region

31. Combining Information Types Region State City A & E Film Theatre Music Restaurants California Eclectic Indian French Assumed task: looking for evening entertainment

32. Combining Collections for Specific Tasks Assumed task: looking for evening entertainment Despite the fact that the query was on restaurants in general Will only help some of the time Very restricted access to related info The UI is very limited hypertext links Doesn’t allow search over entertainment linking back to related restaurants

33. Other Possible Combinations Region + A&E City + Restaurant + Movies City + Weather City + Education: Schools Restaurants + Schools …

34. Bookstore preview combinations topic + related topics topic + publications by same author topic + books of same type but related topic

35. Combining Information Types: Information “Appliances” Palm Pilot Sweet spot Suite spot Smart Cars Driving directions, traffic conditions Nearby restaurants Car status, gas stations, nearby repair shops Indy 500 results? Smart Coffee Maker When to brew, warm up, turn off Coffee futures in Brazil?

36. The Importance of Informative Previews Jared Spool’s studies (www.uie.com) More clicks are ok if The “scent” of the target does not weaken If users feel they are going towards, rather than away, from their target.

37. The Importance of Informative Previews How to indicate “scent”? Information organization reflects tasks Longer, more descriptive links Show category subtopic information Breadth vs. depth tradeoffs CNN categores (more scrolling) vs. Yahoo’s (more clicking) Menu studies Larson & Czerwinski study Intermediate breadth vs. depth generally best

38. Showing Where You’re Going

41. Simplicity / Flexibility Tradeoff Wizard Hyperlinks (categories) Search results + related docs / words Search results + related metadata increasing flexibility

42. Spreadsheets Highly flexible Several operators Many orders to use & combine them in What gets used?(Nardi 93) Most people learn a very limited subset of operations, use these in stereotyped ways Most groups depend on local experts

43. Problem with Previews Problems with Previews Hand edited, predefined Not personalized Not dynamic Should users edit these themselves?

44. Personalizing Combinations Mobile People Architecture (M. Baker) Route information to the right device, with the right resolution, at the right time Examples: Stop phones from ringing in empty offices, or at home during dinner Convert voice to email or video to voice, etc. Uses condition-action rules to combine: Sender Recipient Sender Media types Receiver Media types Time of day Words in title Words in body of message

45. Personalized Condition-Action Rules (From Roussopoulos et al, USITS 99)

46. Personalized Condition-Action Rules Problems: Complex Brittle Who puts them together? The user? A human editor? The system? What are the right criteria? Easier for common or stereotypical scenarios Difficult for information-intense processes

47. Dynamic Previews Flamenco project Preview and postview information determined dynamically and (semi) automatically, based on current task Medical example Allow user to select metadata in any order At each step, show different types of relevant metadata, based on prior steps and personal history, along with # of documents Could not precompute all possible combinations Previews restricted to only those types that might be helpful

48. Medical preview combinations Disease Procedure Side Effects Products HospitalsRegion different metadata types This patient’s allergies

49. Question Answering Ask Jeeves does this by hand One answer per questions Question/answer pairs don’t generalize well Alternative: Use the task to Restrict the kinds of questions being asked Restrict the kinds of answers that are shown

50. DynaCat: An Approach to Task-Specific Q/A By Wanda Pratt (Stanford PhD, now at UC Irvine) Domain: Medicine Collection: Medical research articles Task: Layperson wanting detailed information on a particular aspect of disease Technique: Question types Answers organization based on question type

51. DynaCat Strategy (Pratt, Hearst, & Fagan 99) Identify generally useful question types What is the prognosis for disease D? What are the side-effects of drug P? Identify generally useful categories for the answers Behavior Chemicals & Drugs Use these categories only to organize retrieved documents.

52. DynaCat Screenshot

53. DynaCat Study Design Three queries 24 cancer patients Compared three interfaces ranked list, clusters, categories Results Participants strongly preferred categories Participants found more answers using categories Participants took same amount of time with all three interfaces Another study also favors categories over lists (Chen and Dumais, CHI 2000)

54. Task-sensitive question answering This approach is restricted, but at the same time somewhat general Applicable to thousands of queries Continues to work even if underlying datasets change

55. Specialized UIs The type of information should also structure the interface Chat rooms Legal cases Software documentation How should the type of data influence the type of UI?

56. Conversation Maps, Sack 99

57. Chat histories, Viegas & Donath 99

58. Where you’re going VQUERY (Jones 98)

59. Showing where you’ve been

60. Showing where you’ve been ReadWear (Hill & Hollan 92) Shows which parts of document or collection the user has read or edited and to what degree.

61. Showing Where You’ve Been: PadPrints (Hightower et al. 98)

62. An Additional Problem Assuming we have many task-specific combinations of collections and UIs … … how to get the users to the right ones at the right time?

63. Current Projects CHA-CHA, FLAMENCO: Search Interfaces LINDI: Text Data Mining TANGO: Automated Web Site Usability Assessment

64. Summary Customizable zone architecture: great idea! Task-centric approaches Workspaces Showing next choices / previews Task-sensitive question answering Special search UIs Issues How to build these? Given lots of task-specific UIs, how to find the right one?

65. Context 1. The part of a text or statement that surrounds a particular word or passage and determines its meaning. 2. The circumstances in which an event occurs; a setting. (American Heritage Dictionary)

66. Putting Search Results in Context Visualizations of Query Term Distribution KWIC, TileBars, SeeSoft Visualizing Shared Subsets of Query Terms InfoCrystal, VIBE, Lattice Views Table of Contents as Context Superbook, Cha-Cha, DynaCat Organizing Results with Tables Envision, SenseMaker Using Hyperlinks WebCutter

67. Variations in Flexibility Choice of operators/ combinations Choice of input values hypertext standard GUI spreadsheet standard search wizard

68. Flexibility Differences Standard GUIs Many operations Restricted order of operations Task-centric Completion matters Hypertext One operation (link) Operation order unrestricted Information-centric No natural stopping point

69. Spreadsheets Highly flexible Several operators Many orders to use & combine them in What gets used?(Nardi 93) Most people learn a very limited subset of operations, use these in stereotyped ways Most groups depend on local experts

70. Standard Search Few operators, but Many many input values (words) Results differ widely depending on the values used

71. A simple example: Pre-determined Source Selection Should users be forced to select sources first? Problems Requires an extra set of clicks Users aren’t used to searching on collection descriptions Alternative: decide sources automatically GLOSS system (Tomasic et al. 97) Search portals are deciding a priori (Lycos)