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Incorporating Metadata into Search UIs

Incorporating Metadata into Search UIs

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Incorporating Metadata into Search UIs

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  1. Incorporating Metadata into Search UIs Marti Hearst UC Berkeley

  2. wizard hyperlinks text search The Simplicity / Flexibility Tradeoff

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

  4. How to Control Flexibility? Focus on the task.

  5. 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

  6. 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?

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

  8. How to Incorporate the Task? • Restrict Flexibility in motivated ways: • Restrict collection: Vortals • Restrict suggested search results: Previews

  9. GeoRegion + Time/Date + Topic + Role Metadata types

  10. Two Approaches • Use metadata to select a subset of the collection to search over • Use metadata to suggest where to go next

  11. A simpler example (FindLaw) • Only one topic – law • Many different legal sources

  12. 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

  13. Rather than search as usual across an intersection of metadata types …Information Previews: where to go next

  14. Task-Specific Preview CombinationsA Simple Example Yahoo restaurant guide combines: • Region • Topic (restaurants) • Related Information • Other attributes (cuisines) • Other topics related in place and time (movies)

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

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

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

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

  19. 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

  20. 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

  21. 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.

  22. 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

  23. Problem with Previews • Standard approaches • Hand edited, predefined • Not tailored to task as it develops • Not personalized • Not dynamic

  24. A new project: FLAMENCO FLexible Access using MEtadata in Novel COmbinations • Main idea: • Preview and postview information • Determined dynamically and (semi) automatically, based on current task

  25. 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

  26. Asthma > Steroids • A steroid-induced acute psychosis in a child with athsma. • 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. …

  27. Asthma > Steroids > Admin & Dosage • Dosage levels for asthmatic steroids: A survey. • Related Categories • Inhalators (40) • Emotional Effects (25) • Preferred Suppliers (30) • User Preferred • Musculoskeletal (0) • Drug Resistance (2) • All Categories (50) • Steroids • Pregnanes • Pregnadienes (3) • Prednisone (5) 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. …

  28. Asthma > Steroids Asthma > Steroids > Budesonide Asthma > Steroids > Budesonide > Huang Asthma > Huang > Budesonide Other paths: back up and go forward

  29. 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

  30. 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

  31. Summary • Standard search is too flexible • Hyperlinks 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?