Flexible Search and Navigation using Faceted Metadata

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Flexible Search and Navigation using Faceted
Metadata

• Prof. Marti Hearst
• University of California, Berkeley
• Search Engines Meeting, April 2002
• Research funded by
• NSF CAREER Grant, NSF IIS-9984741

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The Flamenco Project Team

• Ame Elliott
• Jennifer English
• Marti Hearst
• Rashmi Sinha
• Kirsten Swearingen
• Ping Yee
• http//bailando.sims.berkeley.edu/flamenco.html

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Motivation

• Web search works well now
• Gets people to the appropriate web sites
• Finds starting points
• Web SITE search is NOT ok
• Results still overwhelming
• Not well-integrated with the information
  architecture
  
• People prefer to follow links anyhow

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Recent Study by Vividence Research

• Spring 2001, 69 web sites
• 70 eCommerce
• 31 Service
• 21 Content
• 2 Community
• The most common problems
• 53 had poorly organized search results
• 32 had poor information architecture
• 32 had slow performance
• 27 had cluttered home pages
• 25 had confusing labels
• 15 invasive registration
• 13 inconsistent navigation

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Following Hyperlinks

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

Free Text Search

• Can specify anything
• Can result in a disorganized mess

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An Analogy
hypertext
Wanted An All TerTrain Vehicle!
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Main Idea

• Integrate the search seamlessly into the
  information architecture
  
• Use hierarchical metadata to
• Allow flexible navigation
• Provide query previews
• Organize search results
• Both expand and refine the search

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The Challenges

• Users dont like new search interfaces
• How to show lots more information without
  overwhelming or confusing?

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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
  

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An Important Trend in Information Architecture
Design

• Generating web pages from databases
• Implications
• Web sites can adapt to user actions
• Web sites can be instrumented

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A Taxonomy of WebSites
high
Complexity of Data
low
low
high
Complexity of Applications
From The (Short) Araneus Guide to Website
development, by Mecca, et al,
Proceedings of WebDB99, http//www-rocq.inria.fr/
cluet/WEBDB/procwebdb99.html
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Faceted Metadata
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Metadata data about dataFacets orthogonal
categories
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Faceted Metadata Biomedical MeSH (Medical
Subject Headings)www.nlm.nih.org/mesh
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Mesh Facets (one level expanded)
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Questions we are trying to answer

• How 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?

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How NOT to do it

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

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Yahoos use of facets
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Yahoos use of facets
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Yahoos use of facets
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Yahoos 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
  

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Problem with Metadata Previews as Currently Used

• Hand edited, predefined
• Not tailored to task as it develops
• Not personalized
• Often not systematically integrated with search,
  or within the information architecture in
  general
  

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Recipe Collection Examples
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From soar.berkeley.edu (a poor example)
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From www.epicurious.com (a good example)
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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
  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)
  

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Metadata usage in Epicurious
Recipe
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Metadata usage in Epicurious
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Metadata usage in Epicurious
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Metadata usage in Epicurious

I
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Metadata usage in Epicurious

I
Select
Prepare
Cuisine
I
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Recipe Information Architecture

• Information design
• Recipes have five types of metadata categories
• Cuisine, Preparation, Ingredients, Dish,
  Occasion
  
• Each category has one level of subcategories

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Recipe Information Architecture

• Navigation design
• Home page
• show top level of all categories
• Other pages
• A link on an attribute ANDS that attribute to the
  current query results are shown according to a
  category that is not yet part of the query
  
• A change-view link does not change the query, but
  does change which categorys metadata organizes
  the results
  

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Epicurious Basic Search

• Lacks integration with metadata

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Epicurious Usability Study

• People liked the browsing-style metadata-based
  search and found it helpful
  
• People sometimes preferred the advanced search
• For more constrained tasks
• But zero results are frustrating
• People dissprefer the standard simple search

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Missing From Epicurious

• How to scale?
• Hierarchical facets
• Larger collection
• How to integrate search?
• How to allow expansion in addition to refinement?

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Metadata Interface for Image Search
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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

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Architects and City Planners

• Common activitie
• 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 indexes
  
• Do not like to use computers to find images

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The Collection

• 40,000 images from the UCB architecture slide
  library
  
• The current database and interface is called
  SPIRO
  
• Very rich, faceted, hierarchical metadata

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Architects Image Use

• Common activitie
• 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 indexes
  
• Do not like to use computers to find images

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Development Timeline

• Needs 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

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The Interface

• Nine hierarchical facets
• Matrix
• SingleTree
• Chess metaphor
• Opening
• Middlegame
• Endgame
• Tightly Integrated Search
• Expand as well as Refine
• Intermediate pages for large categories

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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 tasks
• Subjective responses
• All highly positive
• Very strong desire to use the interface in
  future
  
• Will replace the current SPIRO interface

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Study Tasks

• 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
  
• Low Constraint Search
• Find a low-constraint set of images (metadata in
  one facet)
  
• Specific Image Search
• Given a photograph and no other info, find the
  same image in the collection
  
• Browse for Images of Interest

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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

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Overall Preferences Matrix vs. Tree
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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.

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User Comments Tree

• Pro
• Simple
• More typical of other search engines Id use
• Visually simpler and more intuitiveMatrix 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.

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Task Completion Times
(Find Image is an artificial task given a photo
and
no other info, find it in the collection.)
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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

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Feature Usage () Refining
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Feature Usage Expanding / Starting Over
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Feature Usage () Types of Actions
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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

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Application to Medline
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Summary and Conclusions
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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

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Summary

• Validating an approach to web site search
• Use hierarchical faceted metadata dynamically,
  integrated with search
  
• Many difficult design decisions
• Iterating and testing was key
• Bits and pieces were there in industry
• The approach is being picked up too
• One is very similar now endeca.com

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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

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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
• Allows different people to add content without
  breaking things
  
• Can make use of standard technology

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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?

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Thank you!
For more information

• bailando.sims.berkeley.edu/flamenco.html