Context, Zones, and Usability

Marti Hearst

UC Berkeley

Inktomi Seminar

April 28, 2000

My Background

Databases

Natural Language Processing

Human-Computer Interaction

User Interfaces for Text Search

TileBars

Scatter/Gather

DynaCat

Cat-a-Cone

Search Interfaces:Past Projects

Common Themes:

Search Result Context

Integrating Browsing & Search

Outline

What are context zones? The importance of the task UI / HCI ideas & projects

Workspaces Information previews Alternative UIs

WWWWWW

Context Zones

IndustryIndustry

IntranetIntranet

DesktopDesktop

Cascading priority based on locality of information

WWWWWW

Context Zones

IndustryIndustry

IntranetIntranet

DesktopDesktop

Specific slice through the data: analyst vs salesperson, or legal vs. medical

WWWWWW

Context Zones

IndustryIndustry

IntranetIntranet

DesktopDesktop

Slice again based on task, e.g., research vs reporting

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

Slicing by Topic Only

Example: FindLaw A vertical slice through legal text

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 6th circuit court of appeals

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?

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)

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?

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).

How to incorporate the task?

Workspaces Relevant information previews Task-sensitive question-answering

Simplicity / Flexibility Tradeoff

Workspace

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

Early Workspaces Xerox PARC

Rooms (Hendersen & Card 86)

Sun/HP X-windows task grouping

Elastic Windows (Kandogan & Shneiderman 97)

Task:General work context

Workspaces

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

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

DLITE (Cousins 97)

Task: Technical research

Sources: Bibliographic

collection, WWW Operators:

Summarize documents

Translate documents Extract references

Query form: Title, Author, Subject

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.

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

Metadata-based Customization

Time/Date Topic RoleGeoRegion

Task-Specific Preview CombinationsA Simple Example

Yahoo restaurant guide combines: Region Topic (restaurants) + Attributes (cuisine) Related Information

Other attributes (cuisines) Other topics related in place and time (movies)

Green: restaurants & attributes

Red: related in place & time

Yellow: region

Combining Information Types

Region State

City

A & E Film Theatre Music Restaurants

California Eclectic Indian French Assumed task: looking for

evening entertainment

Other Possible Combinations

Region + A&E City + Restaurant + Movies City + Weather City + Education: Schools Restaurants + Schools …

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

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?

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.

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

Showing Where You’re Going

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

increasingflexibility

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

Problem with Previews

Problems with Previews Hand edited, predefined Not personalized Not dynamic

Should users edit these themselves?

Personalizing CombinationsMobile 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

Personalized Condition-Action Rules

(From Roussopoulos et al, USITS 99)

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

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

Medical preview combinations

Disease

Procedure

Side Effects

Products

Hospitals Region

differentmetadatatypes

This patient’s allergies

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

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

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.

DynaCat Screenshot

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)

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

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?

Conversation Maps, Sack 99

Chat histories, Viegas & Donath 99

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?

Current Projects

CHA-CHA, FLAMENCO: Search Interfaces

LINDI: Text Data Mining

TANGO: Automated Web Site Usability

Assessment

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?