Incorporating Metadata into Search UIs
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Incorporating Metadata into Search UIs
Marti Hearst and Ame Elliott
GUIR
Summer 2000
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Outline
What’s wrong with search? The Simplicity / Flexibility tradeoff Task-oriented specialization
Vortals Metadata-based Previews
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What’s right with (Web) search?
Easy to get to site home pages Automatic category suggestion
Disambiguates terms Isolates home pages of sites Suggests related information
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What’s wrong with (Web) search?
Too many results Wrong meanings for words Difficult to express complex ideas / goals Doesn’t help on the sites themselves Doesn’t answer questions
Find campsite availability at a particular park Pros and cons of tamoxifen for cancer treatment Find a perfect wooden chest for your niece’s bedroom Find prior art for this patented idea Find a good opthamologist in your area
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The future of search:A Dichotomy
Information Intensive
Business analysis Scientific research Planning & design
Quick lookup Question answering Location-based info
Restaurants Local history
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Next generation search interfaces
More specialized in terms of Tasks Collections Interfaces
Improved Technologies Question-answering Categorization Information previews
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The Simplicity / Flexibility Tradeoff
wizard hyperlinks text search
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Variations in Flexibility
Choice ofoperators/combinations
Choice of input values
hypertext
standardGUI
spreadsheet
standardsearch
wizard
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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
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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
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Standard Search
Few operators (less flexible) Many many input values (more flexible)
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How to Control Flexibility?
Focus on the task.
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The Importance of the Task
Results from HCI suggest the importance of taking the task into account.
Searching patent databases Proving non-infringement Browsing newsgroups Finding the denial-of-service
hacker Getting all satellite news Anticipating the competition
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The Importance of the Task
Example: How does Web page download time effect usability?
In one study, Spool found: (56kbit modem)
Amazon: 36 sec/page (avg) About.com: 8 sec/page (avg)
Users rated the sites: Fastest: Amazon Slowest: About.com
Why?
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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).
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How to Incorporate the Task?
Goal: Look at a work practice. Restrict the search
method to support this task. Two Mechanisms using Metadata
Restrict collection: Vortals Restrict suggested next steps: Previews
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Metadata types
Time/Date Topic RoleGeoRegion
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Restrict the Collection: Vortals
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As Web Grows, Search Degrades
Solution: Specialize the collection
(Vortal = Vertical Portal) Reduces ambiguity of query word usage Eliminates irrelevant information in advance Allows for customization / personalization
Vortal Example: FindLaw A vertical slice through legal text
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WWWWWW
IndustryIndustry
IntranetIntranet
DesktopDesktop
Cascading priority based on locality of information
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WWWWWW
IndustryIndustry
IntranetIntranet
DesktopDesktop
Specific slice through the data: analyst vs salesperson, or legal vs. medical
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WWWWWW
IndustryIndustry
IntranetIntranet
DesktopDesktop
Slice again based on task, e.g., research vs reporting
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A simpler example (FindLaw)
Only one topic – law Many different legal sources
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Slicing by Topic Only
Generic search interface not enough No support for 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
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Rather than search as usual across an intersection of metadata types …
Information Previews: where to go next
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Task-Specific Preview CombinationsA Simple Example
Yahoo restaurant guide combines: Region Topic (restaurants) + Attributes (cuisine) Related Information
Other attributes (ratings) Other topics related in place and time (movies)
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Green: restaurants & attributes
Red: related in place & time
Yellow: geographic region
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Combining Information Types
Region State
City
A & E Film Theatre Music Restaurants
California Eclectic Indian French Assumed task: looking for
evening entertainment
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Other Possible Combinations
Region + A&E City + Restaurant + Movies City + Weather City + Education: Schools Restaurants + Schools …
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Bookstore preview combinations topic + related topics topic + publications by same author topic + books of same type but related topic
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Pre-defined Sources
Decide in advance which collections to show results from
Places search results in context Problem: the same metadata is used for
all queries
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Information previews
Use the 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
Reduces mental work Recognition over recall Suggest alternatives
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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.
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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 categories (more scrolling) vs. Yahoo’s (more clicking) Menu studies Larson & Czerwinski study Intermediate breadth vs.
depth generally best
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Problem with Previews
Standard approaches Hand edited, predefined Not tailored to task as it develops Not personalized Not dynamic
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A new project: FLAMENCOFLexible Access using MEtadata in Novel COmbinations
Main idea: Preview and postview information Determined dynamically and (semi)
automatically, based on current task
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Flamenco: Dynamic Previews
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, include # of documents
Previews restricted to only those metadata types that might be helpful
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Asthma > Steroids
1. A steroid-induced acute psychosis in a child with athsma.2. Management of steroid-dependent asthma with methotrexate.
1. A steroid-induced acute psychosis in a child with athsma.2. Management of steroid-dependent asthma with methotrexate.
Steroids•Pregnanes• Pregnadienes (5)• Prednisone (5)• Pregnenes• Budesonide (4)• Corticosterone (3)
Other Views• Admin & Dosage (50)• Drug Effects (20• Therapeutic Use (25)• Risk Factors (4)• More …
User Preferred• Musculoskeletal (4)•Drug Resistance (6)
•All Categories (99)
99 Documents: [Sort by author] [Sort by popularity] [Sort by Steroids] [Cluster]
1. Effect of short-course budesonide on the bone turnover of asthmatic children.2. Effect of prednisone on response to influenza virus vaccine in asthmatic children.…
1. Effect of short-course budesonide on the bone turnover of asthmatic children.2. Effect of prednisone on response to influenza virus vaccine in asthmatic children.…
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Asthma > Steroids > Admin & Dosage
1. Dosage levels for asthmatic steroids: A survey.1. Dosage levels for asthmatic steroids: A survey.
Steroids•Pregnanes• Pregnadienes (3)• Prednisone (5)
Related Categories•Inhalators (40)•Emotional Effects (25)•Preferred Suppliers (30)
User Preferred• Musculoskeletal (0)•Drug Resistance (2)
•All Categories (50)
50 Documents: [Sort by author] [Sort by popularity] [Sort by Dosage] [Cluster]
1. Optimal dosage levels for prednisone in the treatment of childhood asthma.2. …
1. Optimal dosage levels for prednisone in the treatment of childhood asthma.2. …
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Other paths: back up and go forward
Asthma > Steroids > Budesonide > Huang
Asthma > Huang > Budesonide
Asthma > Steroids
Asthma > Steroids > Budesonide
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Another Application
Finding images for design tasks
See Ame’s talk
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Dynamic Metadata Previews
How different from Yahoo & Amazon? Dynamically determine what to show next
Yahoo’s combos are predefined Amazon’s are also predefined, and limited to taste
and general topic only
A way to seamlessly integrate Related topics User preferences (personalization) Context-sensitivity
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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
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Project Goals
Develop a general understanding of how to usefully incorporate metadata into the search process
Developed user-validated methodology that can be extended to other domains.
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Summary
Standard search is too flexible Hyperlinks are too restrictive Task-centric approaches
Task-specific collections Flamenco: Showing next choices / previews
Issues How to identify tasks? Given lots of task-specific UIs, how to find the right one?