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Phlat

Phlat. Ph ast & ph lexible personal search and organization. Ed Cutrell Microsoft Research Adaptive Systems & Interaction Group. Outline. Personal search today Search with Phlat With: Susan Dumais, Daniel Robbins, Raman Sarin Search/Browse/Filter Tagging Evaluation & Lessons

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Phlat

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  1. Phlat Phast & phlexible personal search and organization Ed CutrellMicrosoft ResearchAdaptive Systems & Interaction Group

  2. Outline • Personal search today • Search with Phlat • With: Susan Dumais, Daniel Robbins, Raman Sarin • Search/Browse/Filter • Tagging • Evaluation & Lessons • Memory Landmarks • Implicit Query

  3. Search in 2004 … • Many locations, interfaces for finding things (e.g., web, mail, local files, help, history, notes) “… the No.1 question we're trying to solve [in Longhorn] is ‘Where's my stuff?’ Right now, file space on any PC is a cesspool. “ Bill Gates, FORTUNE interview, June 23, 2002 • Often slow

  4. Stuff I’ve Seen • In 2001, we built SIS • Deployed to ~3000 people in MSFT • Allowed us to study how people use (& want to use) personal search • Limited prototype but very successful

  5. Search Today • Desktop search hits the bigtime! • MSN Toolbar—Windows Desktop Search • Google DS • Yahoo! Toolbar (X1 DS) • Copernic DS • Apple OS X Tiger with Spotlight • Many others… • Unified index of full-text & metadata for different stores • Re-use vs. initial discovery

  6. Simple UI on Rich Client

  7. Search with Phlat • Phlat asks: Can we design an intuitive and flexible interface that replaces the traditional search/browse dichotomy? • Topple the tyranny of the rigid hierarchical file system!(folders: keep the metadata and toss the metaphor) • Embrace the power of the index!(real-time interaction on any axis) • Powered by Windows Desktop Search • Phlat is a client shell that runs against the index built & maintained by Windows DS (MSN Toolbar) • Queries routed through SIS Communications layer (C#)

  8. Faceted property filtering • 5 canonical properties to filter on (extensible) • Prop filters integrated with query • Type-in for each property (wordwheel) • Search==Browse

  9. Tagging • Apply single set of user-generated metadata to all files, email, etc. • Allow but not require hierarchy • Tags are directly associated with files (NTFS or MAPI props) • Need to hook CFD • Delay associated with query & indexer

  10. Demo

  11. Evaluating Phlat • Internal deployment • ~500 downloads • Users include: program management, test, sales, development, administrative, executives, etc. • Research techniques • Free-form feedback • Questionnaires; Structured interviews • Usage patterns from log data • Gaze tracking studies • Lab studies for richer UI (e.g., timeline, trends)

  12. User Logging • Phlat records a broad range of query characteristics to help us understand the characteristics of usage. • Age of items opened • Characteristics of query and filters used • Number of tags applied • Cycle of query iteration • Special instrumented version for gaze tracking research

  13. Phlat Observations 1(unified access) • Metadata quality is variable • Email: rich, pretty clean • Web: little, not very useful for retrieval • Files: some, but often wrong • Human annotation: don’t depend on it…( but good UI in authoring environments can help) • Memory depends on abstractions • Date is dependent on the object! • Appointment, when it happens • File, when it is changed • Email and Web, when it is seen • People • To, From, Cc, Author, Artist • Document names

  14. Phlat Observations 2(tricky business) • Internet cache & web history are very useful but tricky areas • Cache can be confusing, but re-access is important • Access to temp files is GREAT • Tagging • Hierarchy important for tag organization and cognitive assistance, but flexibility is key (think organic) • MUST make tagging UI ubiquitous and available at inflection points of information consumption • Sharing tricky

  15. Timeline w/ Landmarks • Timeline interface (with Merrie Ringel & Eric Horvitz) • Augmented with landmarks as pointers into human memory • General: holidays, world events • Personal: important photos, appointments • Heuristics or Bayesian models to identify memorable events

  16. Distribution of Results Over Time Search Results • Memory Landmarks • General (world, calendar) • Personal (appts, photos) • <linked by time to results> SIS, Timeline w/ Landmarks

  17. Demo

  18. 30 25 20 Search Time (s) 15 10 5 0 Dates Only Landmarks + Dates Timeline Experiment With Landmarks Without Landmarks

  19. Contextualizing Search • Search is not the end goal … Finding: • Always available search from task bar • Search from within apps • Plug-ins w/ queries to Phlat/Desktop Search • Research pane • Implicit queries • Proactively finding results Using: • e.g., drag/drop, tag, etc.

  20. Implicit Queries Quick searches for people associated with the message and Subject. Background search on top k interesting terms from message, based on user’s index — Score = tfdoc / log(tfcorpus+1) Go to SIS for immediate detailed search. Box autofills with IQ search terms. Top N hits for IQ based on size of window. Open items directly.

  21. IQ Demo

  22. Learn More • Phlat is usable NOW!http://phlat • Design goes well beyond the prototype. Feel free to view spec:http://team/sites/phlat • More info, papers, etc. http://research.microsoft.com/~cutrell • Related projects at MSFT • Memex, Tesla, Longhorn

  23. Thank You!

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