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Faceted Metadata in Image Search & Browsing Using Words to Browse a Thousand Images. Ka-Ping Yee, Kirsten Swearingen, Kevin Li, Marti Hearst Group for User Interface Research UC Berkeley CHI 2003 Research funded by: NSF CAREER Grant IIS-9984741 IBM Faculty Fellowship. Outline.

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Faceted Metadata in Image Search & Browsing Using Words to Browse a Thousand Images


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    1. Faceted Metadata in Image Search & BrowsingUsing Words to Browse a Thousand Images Ka-Ping Yee, Kirsten Swearingen, Kevin Li, Marti Hearst Group for User Interface Research UC Berkeley CHI 2003 Research funded by: NSF CAREER Grant IIS-9984741 IBM Faculty Fellowship

    2. Outline • How do people search and browse for images? • Current approaches: • Keywords • Spatial similarity • Our approach: • Hierarchical Faceted Metadata • Very careful UI design and testing • Usability Study • Conclusions Faceted Metadata in Search

    3. How do people want to search and browse images? Ethnographic studies of people who use images intensely: • Finding specific objects is easy • Find images of the Empire State Building • Browsing is difficult • People want to use rich descriptions. Faceted Metadata in Search

    4. Ethnographic Study • Markkula & Sormunen ’00 • Journalists and newspaper editors • Choosing photos from a digital archive • Searching for specific objects is trivial • Stressed a need for browsing • Photos need to deal with themes, places, types of objects, views • Had access to a powerful interface, but it had 40 entry forms and was generally hard to use; no one used it. Faceted Metadata in Search

    5. Markkula & Sormunen ’00 Faceted Metadata in Search

    6. Query Study • Armitage & Enser ’97 • Analyzed 1,749 queries submitted to 7 image and film archives • Classified queries into a 3x4 facet matrix • Rio Carnivals: Geo Location x Kind of Event • Concluded that users want to search images according to combinations of topical categories. Faceted Metadata in Search

    7. Ethnographic Study • Ame Elliot ’02 • Architects • 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 indexes • Do not like to use computers to find images Faceted Metadata in Search

    8. Current Approaches to Image Search • Keyword based • WebSeek (Smith and Jain ’97) • Commercial web image search systems • Commercial image vendors (Corbis, Getty) • Museum web sites Faceted Metadata in Search

    9. Current Approaches to Image Search • Using Visual “Content” • Extract color, texture, shape • QBIC (Flickner et al. ‘95) • Blobworld (Carson et al. ‘99) • Piction: images + text (Srihari et al. ’91 ’99) • Two uses: • Show a clustered similarity space • Show those images similar to a selected one • Usability studies: • Rodden et al.: a series of studies • Clusters don’t work; showing textual labels is promising. Faceted Metadata in Search

    10. Rodden et al., CHI 2001 Faceted Metadata in Search

    11. Rodden et al., CHI 2001 Faceted Metadata in Search

    12. Rodden et al., CHI 2001 Faceted Metadata in Search

    13. How Best to Support Browsing? • To support serendipity, want to view images that are related along multiple dimensions. • But clusters are not comprehensible. • Instead, allow users to “steer” through the multi-dimensional category space in a flexible manner. Faceted Metadata in Search

    14. Some Challenges • Users don’t like new search interfaces. • How to show lots more information without overwhelming or confusing? Faceted Metadata in Search

    15. Our Approach • Integrate the search seamlessly into the information architecture. • Use proper HCI methodologies. • Use faceted metadata: • More flexible than canned hyperlinks • Less complex than full search • Help users see where to go next and return to what happened previously Faceted Metadata in Search

    16. GeoRegion + Time/Date + Topic Metadata: data about dataFacets: orthogonal categories Faceted Metadata in Search

    17. Hierarchical Faceted Metadata Example: Biological Subject Headings 1.Anatomy [A] 2. Organisms [B] 3. Diseases [C] 4. Chemicals and Drugs [D] 5. Analytical, Diagnostic and Therapeutic Techniques and Equipment [E] 6. Psychiatry and Psychology [F] 7. Biological Sciences [G] 8. Physical Sciences [H] 9. Anthropology, Education, Sociology and Social Phenomena [I] 10. Technology and Food and Beverages [J] 11. Humanities [K] 12. Information Science [L] 13. Persons [M] 14. Health Care [N] 15. Geographic Locations [Z] Faceted Metadata in Search

    18. Hierarchical Faced Metadata 1. Anatomy [A]Body Regions [A01] 2. [B] Musculoskeletal System [A02] 3. [C] Digestive System [A03] 4. [D] Respiratory System [A04] 5. [E] Urogenital System [A05] 6. [F] …… 7. [G] 8. Physical Sciences [H] 9. [I] 10. [J] 11. [K] 12. [L] 13. [M] Faceted Metadata in Search

    19. Hierarchical Faceted Metadata 1. Anatomy [A]Body Regions [A01] Abdomen [A01.047] 2. [B] Musculoskeletal System [A02] Back [A01.176] 3. [C] Digestive System [A03] Breast [A01.236] 4. [D] Respiratory System [A04] Extremities [A01.378] 5. [E] Urogenital System [A05] Head [A01.456] 6. [F] …… Neck [A01.598] 7. [G] …. 8. Physical Sciences [H] 9. [I] 10. [J] 11. [K] 12. [L] 13. [M] Faceted Metadata in Search

    20. Hierarchical Faceted Metadata 1. Anatomy [A]Body Regions [A01] Abdomen [A01.047] 2. [B] Musculoskeletal System [A02] Back [A01.176] 3. [C] Digestive System [A03] Breast [A01.236] 4. [D] Respiratory System [A04] Extremities [A01.378] 5. [E] Urogenital System [A05] Head [A01.456] 6. [F] …… Neck [A01.598] 7. [G] …. 8. Physical Sciences [H] Electronics 9. [I] Astronomy 10. [J] Nature 11. [K] Time 12. [L] Weights and Measures 13. [M] …. Faceted Metadata in Search

    21. Hierarchical Faceted Metadata 1. Anatomy [A]Body Regions [A01] Abdomen [A01.047] 2. [B] Musculoskeletal System [A02] Back [A01.176] 3. [C] Digestive System [A03] Breast [A01.236] 4. [D] Respiratory System [A04] Extremities [A01.378] 5. [E] Urogenital System [A05] Head [A01.456] 6. [F] …… Neck [A01.598] 7. [G] …. 8. Physical Sciences [H] Electronics Amplifiers 9. [I] Astronomy Electronics, Medical 10. [J] Nature Transducers 11. [K] Time 12. [L] Weights and Measures 13. [M] …. Faceted Metadata in Search

    22. Hierarchical Faceted Metadata 1. Anatomy [A]Body Regions [A01] Abdomen [A01.047] 2. [B] Musculoskeletal System [A02] Back [A01.176] 3. [C] Digestive System [A03] Breast [A01.236] 4. [D] Respiratory System [A04] Extremities [A01.378] 5. [E] Urogenital System [A05] Head [A01.456] 6. [F] …… Neck [A01.598] 7. [G] …. 8. Physical Sciences [H] Electronics Amplifiers 9. [I] Astronomy Electronics, Medical 10. [J] Nature Transducers 11. [K] Time 12. [L] Weights and Measures Calibration 13. [M] ….Metric System Reference Standard Faceted Metadata in Search

    23. The Interface Design • Chess metaphor • Opening • Middle game • End game Faceted Metadata in Search

    24. Faceted Metadata in Search

    25. Faceted Metadata in Search

    26. Faceted Metadata in Search

    27. Faceted Metadata in Search

    28. Faceted Metadata in Search

    29. Faceted Metadata in Search

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    31. Faceted Metadata in Search

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    33. The Interface Design • Tightly Integrated Search • Supports Expand as well as Refine • Dynamically Generated Pages • Paths can be taken in any order • Consistent Color Coding • Consistent Backup and Bookmarking • Standard HTML Faceted Metadata in Search

    34. What is Tricky About This? • It is easy to do it poorly • Yahoo directory structure • It is hard to be not overwhelming • Most users prefer simplicity unless complexity really makes a difference • It is hard to “make it flow” • Can it feel like “browsing the shelves”? Faceted Metadata in Search

    35. Project History • Identify Target Population • Architects, city planners • 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: • Developed4 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 Faceted Metadata in Search

    36. Project History • Design / Study Round 3. • New version based on results of Round 2 • Highly positive user response • Identified new user population/collection • Students and scholars of art history • Fine arts images • Study Round 4 • Compare the metadata system to a strong, representative baseline Faceted Metadata in Search

    37. New Usability Study • Participants & Collection • 32 Art History Students • ~35,000 images from SF Fine Arts Museum • Study Design • Within-subjects • Each participant sees both interfaces • Balanced in terms of order and tasks • Participants assess each interface after use • Afterwards they compare them directly • Data recorded in behavior logs, server logs, paper-surveys; one or two experienced testers at each trial. • Used 9 point Likert scales. • Session took about 1.5 hours; pay was $15/hour Faceted Metadata in Search

    38. The Baseline System • Floogle • Take the best of the existing keyword-based image search systems Faceted Metadata in Search

    39. Comparison of Common Image Search Systems Faceted Metadata in Search

    40. sword Faceted Metadata in Search

    41. Faceted Metadata in Search

    42. Faceted Metadata in Search

    43. Faceted Metadata in Search

    44. Evaluation Quandary • How to assess the success of browsing? • Timing is usually not a good indicator • People often spend longer when browsing is going well. • Not the case for directed search • Can look for comprehensiveness and correctness (precision and recall) … • … But subjective measures seem to be most important here. Faceted Metadata in Search

    45. Hypotheses • We attempted to design tasks to test the following hypotheses: • Participants will experience greater search satisfaction, feel greater confidence in the results, produce higher recall, and encounter fewer dead ends using FC over Baseline • FC will perceived to be more useful and flexible than Baseline • Participants will feel more familiar with the contents of the collection after using FC • Participants will use FC to create multi-faceted queries Faceted Metadata in Search

    46. Four Types of Tasks • Unstructured (3): Search for images of interest • Structured Task (11-14): Gather materials for an art history essay on a given topic, e.g. • Find all woodcuts created in the US • Choose the decade with the most • Select one of the artists in this periods and show all of their woodcuts • Choose a subject depicted in these works and find another artist who treated the same subject in a different way. • Structured Task (10): compare related images • Find images by artists from 2 different countries that depict conflict between groups. • Unstructured (5): search for images of interest Faceted Metadata in Search

    47. Other Points • Participants were NOT walked through the interfaces. • The wording of Task 2 reflected the metadata; not the case for Task 3 • Within tasks, queries were not different in difficulty (t’s<1.7, p >0.05 according to post-task questions) • Flamenco is and order of magnitude slower than Floogle on average. • In task 2 users were allowed 3 more minutes in FC than in Baseline. • Time spent in tasks 2 and 3 were significantly longer in FC (about 2 min more). Faceted Metadata in Search

    48. Results • Participants felt significantly more confident they had found all relevant images using FC (Task 2: t(62)=2.18, p<.05; Task 3: t(62)=2.03, p<.05) • Participants felt significantly more satisfied with the results (Task 2: t(62)=3.78, p<.001; Task 3: t(62)=2.03, p<.05) • Recall scores: • Task2a: In Baseline 57% of participants found all relevant results, in FC 81% found all. • Task 2b: In Baseline 21% found all relevant, in FC 77% found all. Faceted Metadata in Search

    49. Post-Interface Assessments All significant at p<.05 except simple and overwhelming Faceted Metadata in Search

    50. Perceived Uses of Interfaces Baseline FC Faceted Metadata in Search