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Bongshin Lee, Greg Smith, George Robertson, Mary Czerwinski, Desney Tan Computational User Experiences (CUE) Visualization and Interaction Research Group.

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Presentation on theme: "Bongshin Lee, Greg Smith, George Robertson, Mary Czerwinski, Desney Tan Computational User Experiences (CUE) Visualization and Interaction Research Group."— Presentation transcript:

1 Bongshin Lee, Greg Smith, George Robertson, Mary Czerwinski, Desney Tan Computational User Experiences (CUE) Visualization and Interaction Research Group Microsoft Research

2 Explore large metadata-rich collections of information Provide a more effective and enjoyable searching and browsing user experience with faceted browsing Show meaningful trends in data Show relationship between items

3 Who has Brad published with? What InfoVis papers did Stu, Jock, and George co-author in 1991? How many times has Hiroshi been cited by CHI papers? How has Ben’s publication pattern changed over the years? History of CHI: Pop Quiz

4 Facet: Grouping of item attributes Multiple paths to any item Faceted Browsing: Integration of facets with dynamic query previews Studies have shown performance and preference advantages (e.g., Flamenco, CHI ’03)

5 FacetMap [InfoVis ‘06] Flamenco [CHI ‘03] Relation Browser++ [Digital Gov. Research ‘05] + many commercial online shopping sites

6 Multiple bar charts IN-SPIRE [InfoVis ‘04] PaperLens [CHI ‘05] NetLens [IVS ‘07] Stacked bar charts ThemeRiver [TVCG ‘02] NameVoyager [InfoVis ‘05] Stacked Graphs [InfoVIs ‘08] + many commercial tools (e.g., Microsoft Excel, Tableau [InfoVis ‘07],...)

7 InfoZoom [DM ‘00] Relation Browser++ [Digital Gov. Research ‘05] Bungee View http://cityscape.inf.cs.cmu.edu/bungee/

8 Faceted BrowsingTrend Vis ++ Additional features…

9 Identify and Compare Trends Attribute values are visually presented in an explicit order (e.g., time)

10 Navigate between Related Items navigate further into related items whether or not filters have been exhausted Enabled by allowing items to be attributes of other items

11 Reveal Relationships Attribute co-occurrence Co-authorship Co-citations When an item can have multiple simultaneous values for the same facet

12 Scaling to Large Datasets All the attribute values often cannot fit in the allocated screen space

13 2 datasets ACM CHI Publications 23 years (1982-2004) 4073 papers & 6300 authors Topics, Authorship, Affiliations, … Find insights Initial overview Simple filtering Further exploration OECD grant data 32 years (1974-2005) about 1M inter-county grants Donors, Recipients, Purposes, … Demo

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15 5 researchers and 1 developer (2 females) ACMCHI Publications dataset 9 tasks begin with simple tasks and then gradually increase complexity 2 tasks consist of 2 sub-tasks 1 task consists of 3 sub-tasks Lasted about 30 minutes

16 1. Which author publishes the most frequently in the topic of CSCW? 2. What are the affiliations of the two authors from China? 3. a. How many papers did Irene Grief author? b. Which year did she publish the most? 4. Which co-author did Brad Myers publish with most frequently? 5. In what year was Hiroshi Ishii cited by the most papers? 6. a. Who was Ben Shneiderman’s most frequent coauthor in the Info Vis topic area? b. How many papers did they publish together in Info Vis? c. Which year did they publish the most together? 7. Compare the publication trends for Lab Reports by year and CSCW papers by year. How do they differ? 8. a. Find the authors of the paper “The Perspective Wall.” Which states did they live in? b. Pivot to the papers authored by Jock Mackinlay. Which paper did his papers cite the most? 9. Describe three facts about Randy Pausch. User study tasks

17 Overall, easy to use Easy, Useful and Interesting Trend visualization Drag and drop interaction Attribute search within the facets Missing: undo Semantics of facets are difficult to express Symmetric relationship Multi-value facets

18 FacetLens supports exploration of a large faceted datasets by exposing trends and relationships Future Work Improve navigation Paper & Author vs. Paper-centric Scale to larger datasets Longitudinal study

19 http://research.microsoft.com/cue/facetlens


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