SIMS 213: User Interface Design & Development

Marti HearstThurs, March 14, 2002

Outline: Site Search Interfaces

1. Motivation2. Approach

Integrate Search into Information Architecture via Faceted Metadata3. Definitions:

Information Architecture Faceted Metadata

4. Recipe Interface and Usability Study5. Image Interfaces and Usability Studies6. Conclusions

Motivation and Background

Claims

Web Search is OK– Gets people to the right starting points

Web SITE search is NOT okThe best way to improve site search is– NOT to make new fancy algorithms– Instead … improve the interface

The Philosophy

Information architecture should be designed to integrate search throughoutSearch results should reflect the information architecture.

This supports an interplay between navigation and searchThis supports the most common human search strategies.

An Important Search Strategy

Do a simple, general search– Gets results in the generally correct area

Look around in the local space of those resultsIf that space looks wrong, start over– Akin to Shneiderman’s overview + details

Our approach supports this strategy– Integrate navigation with search

Following Hyperlinks

Works great when it is clear where to go nextFrustrating when the desired directions are undetectable or unavailable

An Analogy

text searchhypertext

Main Idea

Use metadata to show where to go next– More flexible than canned hyperlinks– Less complex than full search– Help users see and return to what happened

previously

Search Usability Design Goals

1. Strive for Consistency2. Provide Shortcuts3. Offer Informative Feedback4. Design for Closure5. Provide Simple Error Handling6. Permit Easy Reversal of Actions7. Support User Control8. Reduce Short-term Memory Load

From Shneiderman, Byrd, & Croft, Clarifying Search, DLIB Magazine, Jan 1997. www.dlib.org

A Taxonomy of WebSites

low

low

high

high

Complexity of Applications

Complexity of Data

From: The (Short) Araneus Guide to Website development, by Mecca, et al, Proceedings of WebDB’99, http://www-rocq.inria.fr/~cluet/WEBDB/procwebdb99.html

Catalog SitesWeb-based Information

Systems

Web-Presence Sites

Service-Oriented Sites

An Important IA Trend

Generating web pages from databasesImplications:– Web sites can adapt to user actions– Web sites can be instrumented

Faceted Metadata

Metadata: data about dataFacets: orthogonal categories

Time/Date TopicGeoRegion

Faceted Metadata: Biomedical MeSH (Medical Subject Headings)

www.nlm.nih.org/mesh

Mesh Facets (one level expanded)

Questions we are trying to answerHow many facets are allowable?Should facets be mixed and matched?How much is too much?Should hierarchies be progressively revealed, tabbed, some combination?How should free-text search be integrated?

How NOT to do it

Yahoo uses faceted metadata poorly in both their search results and in their top-level directoryThey combine region + other hierarchical facets in awkward ways

Yahoo’s use of facets

Yahoo’s use of facets

Yahoo’s use of facets

Yahoo’s use of facets

Where is Berkeley? College and University > Colleges and Universities >United States > U > University of California > Campuses > Berkeley

U.S. States > California > Cities >Berkeley > Education > College and University > Public > UC Berkeley

Recipe Collection Examples

From soar.berkeley.edu (a poor example)

From www.epicurious.com (a good example)

Epicurious Metadata UsageAdvantages– 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 + event type), • “How can I use an avocado in a salad?'' (ingredient type + dish type), • “How can I bake sea-bass'' (preparation type + ingredient type)

Metadata usage in Epicurious

PrepareCuisineIngredient Dish

Recipe

Metadata usage in Epicurious

PrepareCuisineIngredient Dish

PrepareCuisineDishISelect

Metadata usage in Epicurious

PrepareCuisineIngredient Dish

I >

Group by

PrepareCuisineDish

Metadata usage in Epicurious

PrepareCuisineIngredient Dish

PrepareCuisineDishI >

Group by

Metadata usage in Epicurious

PrepareCuisineIngredient Dish

PrepareCuisineDishI >

Group by

PrepareCuisineISelect

Epicurious Basic SearchLacks integration with metadata

Usability Study: Epicurious

Epicurious Usability Study

9 participantsThree interfaces– Simple search form – Enhanced search form– Browse

Two task types – known-item search – browsing for inspiration

Epicurious Usability Study: Preference Data

Site Basic Enhanced BrowseTotal "Very Likely" to Use: 7 2 4 7

Total "Likely" to Use: 0 1 1 0Total "Not Likely" to Use: 2 6 4 2

Epicurious Usability StudyInterface Preference

FavoriteSubject_JG: EnhancedSubject_NS: EnhancedSubject_SP: Browse

Subject_RM: Browse

Subject_LA: Enhanced

Subject_MC: BrowseSubject_MW: BrowseSubject_NM: EnhancedSubject_CG: Browse

Query previews and navigation. Options to refine by course or season. Choose how you view the results

Searching within made all the difference. I could see how many results I was getting in each Very specific. I can choose more than 1 detail with search for recipe I'm looking for.Likes the way it narrows things down. And it gives you the numbers.

Found it simpler, more readable. Helped you hone in on the season.Liked the kid friendly, low fat optionWhy?

Can narrow down when you're stuck. You can always refine [your search].

Allowed me to make specific selections. I liked Browse too. Gave lots to choose from. Depends on what you’re looking for that day

Can limit and unlimit and limit again in a different way. Prioritize your criteria--change the first thing I clicked and go in a different direction. Easy to back up.

Epicurious Usability StudyFeature Preference

Epicurious Usability StudyConstraint-based Preferences

# of Results High LowEnhanced (LA) Browse (LA)Enhanced (MC) Browse (MC)Browse (MW) Browse (MW)Enhanced (NM) Enhanced (NM)Basic (CG) Browse (CG)Enhanced (LA) Browse (LA)Enhanced (MC) Browse (MC)Enhanced (MW) Browse (MW)Enhanced (NM) Enhanced (NM)Enhanced (CG) Browse (CG)

Constraint

1 result needed

Many results needed

Usability Study Results: Summary

People liked the browsing-style metadata-based search and found it helpfulPeople sometimes preferred the metadata search when the task was more constrained – But zero results are frustrating– This can be alleviated with query previews

People dis-prefer the standard simple search

Missing From Epicurious

How to scale?– Hierarchical facets– Larger collection

How to integrate search?How to allow expansion in addition to refinement?

Application to Image Search

Current Approaches to Image Search

Visual Content and Cues, e.g.,• QBIC (Flickner et al. ‘95)• Blobworld (Carson et al. ‘99)• Body Plans (Forsyth & Fleck ‘00)

– Color, texture, shape– Move through a similarity space

Keyword based– Piction (Srihari ’91)– WebSeek (Smith and Jain ’97)– Google image search

A Commonality Among Current Content-based Approaches:

Emphasis on similarityLittle work on analyzing the search needs

The Users

Architects and City Planners

The Collection

~40,000 images from the UCB architecture slide libraryThe current database and interface is called SPIROVery rich, faceted, hierarchical metadata

Architects’ Image Use

Common activities:– Use images for inspiration

• Browsing during early stages of design– Collage making, sketching, pinning up on walls– This is different than illustrating powerpoint

Maintain sketchbooks & shoeboxes of images– Young professionals have ~500, older ~5k

No formal organization scheme– None of 10 architects interviewed about their image collections

used indexesDo not like to use computers to find images

Development StepsNeeds assessment. – Interviewed architects and conducted contextual inquiries.

Lo-fi prototyping. – Showed paper prototype to 3 professional architects.

Design / Study Round 1. – Simple interactive version. Users liked metadata idea.

Design / Study Round 2: – Developed 4 different detailed versions; evaluated with 11 architects;

results somewhat positive but many problems identified. Matrix emerged as a good idea.

Metadata revision. – Compressed and simplified the metadata hierarchies

Design / Study Round 3. – New version based on results of Round 2– Highly positive user response

The Interface

Nine hierarchical facets– Matrix– SingleTree

Chess metaphor– Opening– Middlegame– Endgame

Tightly Integrated SearchExpand as well as RefineIntermediate pages for large categories

Usability Study on Round 3

19 participants– Architecture/City Planning background

Two versions of the interface– Tree (one hierarchical facet at a time)– Matrix (multiple hierarchical facets)

Several tasksSubjective responses– All highly positive– Very strong desire to use the interface in future– Will replace the current SPIRO interface

Study Tasks1. High Constraint Search:

Find images with metadata assigned from 3 facets(e.g., exterior views of temples in Lebanon)

1.1)       Start by using a Keyword Search 1.2)       Start by Browsing (clicking a hyperlink) 1.3)       Start by using method of choice

2. Low Constraint Search: Find a low-constraint set of images (metadata in one facet)

3. Specific Image Search: Given a photograph and no other info, find the same image in the collection

4. Browse for Images of Interest

Interface Evaluation

Users rated Matrix more highly for:– Usefulness for design work– Seeing relationships between images– Flexibility– Power

On all except “find this image” task, users also rated the Matrix higher for:– Feeling “on track” during search– Feeling confident about having found all relevant images

Overall Preferences: Matrix vs. Tree

Simple search (e.g. images of deserts)

Complex search (e.g. exteriors of temples in Lebanon)

Find images like

this one

OVERALL PREFERENCE

Matrix 13 14 16 16

Tree 5 4 3 3

User Comments - Matrix

“Easier to pursue other queries from each individual page”“Powerful at limiting and expanding result sets. Easy to shift between searches.”“Keep better track of where I am located as well as possible places to go from there.”“Left margin menu made it easy to view other possible search queries, helped in trouble-shooting research problems.”“Interface was friendlier, easier, more helpful.”“I understood the hierarchical relationships better.”

User Comments – Tree

Pro– “Simple”– “More typical of other search engines I’d use”– “Visually simpler and more intuitive…Matrix a bit overwhelming with

choices.”

Con– “I found SingleTree difficult to use when I had to refine my search on a

search topic which I was not familiar with. I found myself guessing.” – “SingleTree required more thought to use and to find specific images.”– “I do not trust my typng and spelling skills. I like having categories.”

Task Completion Times

(Find Image is an artificial task: given a photo andno other info, find it in the collection.)

When Given A Choice …

For each interface, one task allowed the user to start with either a keyword search or the hyperlinks.

3 chose to search in both interfaces

11 chose to browse in both interfaces

4 chose to search in Matrix, browse in Tree

1 chose to browse in Matrix, search in Tree

Precision and Recall

Computed for tasks 1.1-1.3Pooling used for determining relevant setPrecision based on what was visible on screen

Feature Usage

Percentages

(Dark bars show subtotals)

Feature Usage (%) Types of Actions

Action Categories

0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00%

Refine search (reduce# of results)

Expand search(increase # of results)

Arrange results

Start over/backup

Matrix

Tree

Feature Usage (%) Refining

Use of Features to Refine Search

0.00% 5.00% 10.00% 15.00% 20.00% 25.00% 30.00%

Drill above images

Drill in matrix

Drill from image detail

Drill from large category

Drill by clicking "All N items"

Search within

Disambiguate keyword search

"More" in disambiguation

Matrix

Tree

Feature Usage – Expanding / Starting Over

Use of Features to Expand Search / Start Over

0.00% 5.00% 10.00% 15.00% 20.00% 25.00%

Expand search usingbreadcrumbs

Expand by clicking X

Expand from imagedetail

Go back to start mid-search

Search all, mid-task

Back

Matrix

Tree

Interface Evaluation

Users rated Matrix more highly for:– Usefulness for design work– Seeing relationships between images– Flexibility– Power

On all except “find this image” task, users also rated the Matrix higher for:– Feeling “on track” during search– Feeling confident about having found all relevant images

Application to Medline

Summary

A new approach to web site search– Use hierarchical faceted metadata dynamically,

integrated with search

Many difficult design decisions– Iterating and testing was key

Summary

Two Usability Studies Completed– Recipes: 13,000 items– Architecture Images: 40,000 items

Conclusions:– Users like and are successful with the dynamic faceted

hierarchical metadata, especially for browsing tasks– Very positive results, in contrast with studies on earlier

iterations– Note: it seems you have to care about the contents of the

collection to like the interface

Summary

We have addressed several interface problems:– How to seamlessly integrate metadata previews with search

• Show search results in metadata context• “Disambiguate” search terms

– How to show hierarchical metadata from several facets • The “matrix” view• Show one level of depth in the “matrix” view

– How to handle large metadata categories• Use intermediate pages

– How to support expanding as well as refining• Still working on it to some extent

Advantages of the Approach

Supports different search types– Highly constrained known-item searches– Open-ended, browsing tasks – Can easily switch from one mode to the other

midstream– Can both expand and refine

Advantages of the Approach

Honors many of the most important usability design goals– User control– Provides context for results– Reduces short term memory load– Allows easy reversal of actions– Provides consistent view

Advantages of the Approach

Allows different people to add content without breaking thingsCan make use of standard technology

Some Unanswered Questions

How to integrate with relevance feedback (more like this)?– Would like to use blobworld-like features

How to incorporate user preferences and past behavior?How to combine facets to reflect tasks?