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Faceted Metadata in Search Interfaces

Faceted Metadata in Search Interfaces Marti Hearst UC Berkeley School of Information This Research Supported by NSF IIS-9984741. Focus: Search and Navigation of Large Collections Shopping Sites Digital Libraries E-Government Sites Image Collections

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Faceted Metadata in Search Interfaces

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  1. Faceted Metadata in Search Interfaces Marti HearstUC Berkeley School of Information This Research Supported by NSF IIS-9984741.

  2. Focus: Search and Navigation of Large Collections Shopping Sites Digital Libraries E-Government Sites Image Collections Example: the University of California Library Catalog

  3. Web Sites and Collections A report by Forrester research in 2001 showed that while 76% of firms rated search as “extremely important” only 24% consider their Web site’s search to be “extremely useful”. Johnson, K., Manning, H., Hagen, P.R., and Dorsey, M. Specialize Your Site's Search. Forrester Research, (Dec. 2001), Cambridge, MA; www.forrester.com/ER/Research/Report/Summary/0,1338,13322,00

  4. What do we want done differently? • Organization of results • Hints of where to go next • Flexible ways to move around • … How to structure the information?

  5. The Problem With Hierarchy • Forces a choice of one dimension vs another • Either you commit to one path, • Or you have to provide many redundant combinations • Examples • Each topic followed by all time periods followed by all locations AND • Each topic followed by all locations followed by all time periods AND • Each location followed by all topics followed by all time periods … etc

  6. The Problem with Hierarchy

  7. The Problem with Hierarchy

  8. The Problem with Hierarchy

  9. The Problem with Hierarchy

  10. The Problem with Hierarchy

  11. The Problem with Hierarchy

  12. How to Structure Information for Search and Browsing? • Hierarchy is too rigid • Full meaning is too compex • Hierarchical faceted metadata: • A useful middle ground

  13. GeoRegion + Time/Date + Topic + Role What are facets? • Sets of categories, each of which describe a different aspect of the objects in the collection. • Each of these can be hierarchical. • (Not necessarily mutually exclusive nor exhaustive, but often that is a goal.)

  14. Cooking Method Ingredient Stir-fry Chicken Red Bell Pepper Course Curry Cuisine Main Course Thai Facet example: Recipes

  15. Example of Faceted Metadata:Categories for Biomedical Journal Articles 1. Anatomy [A] 2. Organisms [B] 3. Diseases [C] 4. Chemicals and Drugs [D] 1. Lung 2. Mouse 3. Cancer 4. Tamoxifen

  16. Goal: assign labels from facets

  17. Clothing Hats Cowboy Hat Nature Animal Mammal Horse Media Engraving Wood Eng. Occupations Cowboy Location North America America Motivation Description: 19th c. paint horse; saddle and hackamore; spurs; bandana on rider; old time cowboy hat; underchin thong; flying off.

  18. Motivation By using facets, what we are not capturing? The hat flew off; The bandana stayed on. The thong is part of the hat. The bandana is on the cowboy (not the horse). The saddle is on the horse (not the cowboy). Description: 19th c. paint horse; saddle and hackamore; spurs; bandana on rider; old time cowboy hat; underchin thong; flying off.

  19. Hierarchical Faceted Metadata • A simplification of knowledge representation • Does not represent relationships directly • BUT can be understood well by many people when browsing rich collections of information.

  20. How to Use in an Interface? • Users don’t like new search interfaces. • How to show lots of information without overwhelming or confusing? • There are many ways to do it wrong. • Say I want unabridged nonfiction audiobooks • Audible.com, BooksOnTape.com, and BrillianceAudio: • no way to browse a given category and simultaneuosly select unabridged versions • Amazon.com: • has finally gotten browsing over multiple kinds of features working; this is a recent development • but still restricted on what can be added into the query

  21. A Solution (The Flamenco Project) • Incorporating Faceted Hierarchical Metadata into Interfaces for Large Collections • Key Goals: • Support integrated browsing and keyword search • Provide an experience of “browsing the shelves” • Add power and flexibility without introducing confusion or a feeling of “clutter” • Allow users to take the path most natural to them • Method: • User-centered design, including needs assessment and many iterations of design and testing

  22. Nobel Prize Winners Collection

  23. Faceted Metadata Approach

  24. Art History Images Collection

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