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06 November 2007

Human-Information Interaction. Scott Klemmer ta s: Marcello Bastea-Forte, Joel Brandt, Neil Patel, Leslie Wu, Mike Cammarano. 06 November 2007. Questions about the Project. Engelbart Video. Form Me to You. 10 7 (months) SOCIAL Social Behavior 10 6 (weeks) 10 5 (days)

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06 November 2007

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  1. Human-Information Interaction Scott Klemmertas: Marcello Bastea-Forte, Joel Brandt,Neil Patel, Leslie Wu, Mike Cammarano 06 November 2007

  2. Questions about the Project

  3. Engelbart Video

  4. Form Me to You

  5. 107 (months) SOCIAL Social Behavior 106 (weeks) 105 (days) 104 (hours) RATIONAL Adaptive Behavior 103 102 (minutes) 101 COGNITIVE Immediate Behavior 100 (seconds) 10-1 10-2 BIOLOGICAL 10-3 (msec) 10-4 ADAPTIVE BEHAVIOR Meg Stewart

  6. HUMAN INFORMATION INTERACTION

  7. GOMS • Routine cognitive skill • Well-known path

  8. Problem solving Heuristic search Exponential if don’t know what to do Information Search

  9. Optimal Foraging Theory Information Foraging Theory OPTIMALITY THEORY Information Energy [ ] [ ] Energy Time Useful info Time Max Max

  10. Information Foraging Theory: Microeconomics of information access. People are information rate maximizers of benefits/costs Information has a cost structure

  11. e.g. desk piles, Alta vista search list unlike animals foraging for food, humans can do patch construction INFORMATION PATCHES

  12. We’ll stay in a patch longer… When a patch is highly profitable As distance between patches increases When the environment as a whole is less profitable

  13. perception of value and cost of a path to a source based on proximal cues WITHIN-PATCH ENRICHMENT:INFORMATION SCENT

  14. Relevance-Enhanced Thumbnails • Within-patch enrichment • Emphasize text that is relevant to query • Text callouts Allison Woodruff

  15. 100 80 Linear Exponential 60 Number of Pages Visited per Level 40 20 0 0 0.05 0.1 0.15 0.2 f 150 150 Probability of choosing wrong link (f) PHASE TRANSITION IN NAVIGATION COSTS AS FUNCTION OF INFORMATION SCENT .150 .150 100 100 Number of pages visited .125 50 50 .100 .100 0 0 0 0 2 2 4 4 6 6 8 8 10 10 Depth Notes: Average branching factor = 10 Depth = 10

  16. IMPORTANCE FOR WEB DESIGN Jarad Spool, UIE

  17. Peter Pirolli

  18. MACHINE MODELING OF INFORMATION SCENT new cell Information Goal medical patient Link Text treatments dose procedures beam

  19. PREDICTION OF LINK CHOICE 50 35 (b) Yahoo (a) ParcWeb 30 40 25 Predicted frequency 30 20 R2= 0.72 Predicted frequency 15 20 10 R2= 0.90 10 5 0 0 0 10 20 30 40 50 0 5 10 15 20 25 30 35 Observed frequency Observed frequency

  20. Determine relevance of documents Calculate Pr(Link Choice) for each page Examine user patterns Start users at page Flow users through the network .5 .3 .2 User need (vector of goal concepts) USER FLOW MODEL

  21. SENSE MAKING TASKS • Characteristics • Massive amounts of data • Ill-structured task • Organization, interpretation, insight needed • Output, decision, solution required • Examples • Understanding a health problem and making a medical decision • Buying a new laptop • Weather forecasting • Producing an intelligence report

  22. Importance of Sensemaking • 75% of “significant tasks” on the Web are more than simple “finding” of information (Morrison et al., 2001) • Understanding a topic (e.g., about health) • Comparing/choosing products • Information retrieval does not support these tasks (Bhavnani et al., 2002) • E.g., Estimated that one must visit 25 Web pages in order to read about 12 basic concepts about skin cancer

  23. Reevaluate PRESENTATION Search for Support HYPOTHESES SENSEMAKING Tell Story Search for Evidence SCHEMAS Build Case Search for Relations EVIDENCE FILE STRUCTURE Schematize Search for Information SHOEBOX Read & Extract EXTERNAL DATA SOURCES Search & Filter TIME or EFFORT

  24. Foraging Loop Sensemaking Loop Reevaluate PRESENTATION Search for Support HYPOTHESES SENSEMAKING Tell Story Search for Evidence SCHEMAS Build Case Search for Relations EVIDENCE FILE STRUCTURE Schematize Search for Information SHOEBOX Read & Extract EXTERNAL DATA SOURCES Search & Filter TIME or EFFORT

  25. Credits & Further Reading This lecture draws heavily on Stu Card’s slides on HII Peter Pirolli, Information Foraging

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