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Search Text Mining Web Site Usability

Search Text Mining Web Site Usability. Marti Hearst SIMS. BAILANDO Projects. Better Access to Information using Language Analysis and Novel Dynamic Organizations. Current BAILANDO Projects. CHA-CHA: Web Search results in Context LINDI: UI support for Search Text Data Mining

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Search Text Mining Web Site Usability

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  1. SearchText MiningWeb Site Usability Marti Hearst SIMS UCB HCC Retreat

  2. BAILANDO Projects Better Access to Information using Language Analysis and Novel Dynamic Organizations UCB HCC Retreat

  3. Current BAILANDO Projects • CHA-CHA: • Web Search results in Context • LINDI: • UI support for Search • Text Data Mining • TANGO: • Automated Web Site Usability UCB HCC Retreat

  4. Search UIs Combine Browsing & Search Place Search Results in Context Large Category Hierarchies UCB HCC Retreat

  5. Cha-Cha Students: Mike Chen, Jamie Laflen, Jason Hong, Jimmy Lin, Shiang Chen UCB HCC Retreat

  6. Medical Category Hierarchy UCB HCC Retreat

  7. DynaCat (Pratt, Hearst, & Fagan 99) UCB HCC Retreat

  8. DynaCat Study • Design • Three queries • 24 cancer patients • Compared three interfaces • ranked list, clusters, categories • Results • Participants strongly preferred categories • Participants found more answers using categories • Participants took same amount of time with all three interfaces • Similar results have been verified by another study by Chen and Dumais (CHI 2000) UCB HCC Retreat

  9. Cat-a-Cone Interface(Hearst & Karadi 97)

  10. Improving Search via Large Category Hierarchies • How to show intersections across category types? • How to preview related categories in a user-tailored, dynamic manner? UCB HCC Retreat

  11. Information retrieval Text Data Mining UCB HCC Retreat

  12. Information retrieval Selection or rejection of existing documents based on a function of word match. UCB HCC Retreat

  13. Text Data Mining Relationships between information in documents can create new facts, not previously known. UCB HCC Retreat

  14. Imagine You are a medical researcher Your patient has spinal inflammation numbness in fingers low TC levels negative results for all tests How can you help her? UCB HCC Retreat

  15. Idea A new way of searching text. Link pieces of information together to formulate hypotheses … UCB HCC Retreat

  16. LINDILinking Information for New DIscoveries • Students: Barbara Rosario, David Blei • Three main parts • Search UI for building and reusing hypothesis seeking strategies. • Statistical language analysis techniques for interpreting the text. • Backend for interfacing with various databases and translating different formats. UCB HCC Retreat

  17. Gathering Evidence Spinal Inflammation Numbness in fingers Low TC Levels UCB HCC Retreat

  18. Gathering Evidence Find diseases associated with each Spinal Inflammation Numbness in fingers Low TC Levels UCB HCC Retreat

  19. Spinal Inflammation Numbness in fingers Low TC Levels Supporting Cascaded Search Operations UCB HCC Retreat

  20. UCB HCC Retreat

  21. New Language Analysis • First use category labels to retrieve candidate documents • Then use language analysis to detect causal relationships between concepts • Title: • Magnesum deficiency implicated in increased stress levels. • Interpretation: • <nutrient><reduction> related-to <increase><symptom> • Use these to find relationships and formulate hypotheses UCB HCC Retreat

  22. Statistical Semantic Parsing • Modern statistical techniques • Mainly applied to syntactic structure • Probabilistic knowledge representation • Represent hypotheses with different degrees of certainty. UCB HCC Retreat

  23. Automating Assessment of Web Site Usability UCB HCC Retreat

  24. Why Worry? • Problem: IBM's extranet • Heavy use of help and search • Unhappy users • Solution • Massive web site redesign • Focus on info-organization, not the purchasing process. • Cost: "in the millions" • Results • Not announced or trumped up • Use of "help" decreased 84% • Sales increased 400% UCB HCC Retreat

  25. Web TANGOTool for Assessing NaviGation & Organization Student: Melody Ivory • Goal: automated support for comparing design alternatives • How: Assess usability of the information architecture • Approximate people’s information-seeking behavior (Monte Carlo simulation) • Output quantitative usability metrics UCB HCC Retreat

  26. Information Architecture Information Design Navigation Design Graphic Design Courtesy of Mark Newman Anatomy of Web Site Design UCB HCC Retreat

  27. Usability EvaluationStandard Techniques • User studies • Have people use the interface to complete some tasks • Requires an implemented interface • "Discount" vs. Scientific Results • Heuristic Evaluation • An expert assesses a design or implementation according to certain guidelines UCB HCC Retreat

  28. Automated Usability Evaluation • Logging/capture • Pro: Easy • Con: Requires implemented system • Con: Don't know the user task (web) • Con: Don't present alternatives • Con: Don't distinguish error from success • Analytical Modeling • Pro: doable at design phase • Con: models an expert • Con: academic exercise • Simulation UCB HCC Retreat

  29. Existing Metrics • Web metric analysis tools report on what is easy to measure, e.g.: • Predicted download time • Depth/breadth of site • We want to worry about • Content • User goals/tasks • Not available from logs • We also want to compare alternative designs. UCB HCC Retreat

  30. Monte Carlo Simulation • Have a model of information structure • Have a set of user goals • Want to assess navigation structure • Compare alternatives/tradeoffs • Identify bottlenecks • Identify critically important pages/links • Check all pairs of start/end points • Check overall reachability before and after a change. UCB HCC Retreat

  31. Monte Carlo Simulation • At each step in the simulation • Assume a probability distribution over a set of next choices. • The next choice is a function of: • The current goal • The understandability of the choice • The overall complexity of the set of choices • Prior interaction history • These can use models of "scent" • Varying the distribution corresponds to varying properties of the links • Spot-check important choices UCB HCC Retreat

  32. X One Monte Carlo simulation step for Design 1, Task 1. Simulation starts from the home page and the target information is at Renter Support. UCB HCC Retreat

  33. X Monte Carlo simulation results for Design 1, Task 1. Simulation runs start from all pages in the site. Average Navigation times are shown for Tasks 2 & 3. UCB HCC Retreat

  34. Using Simulator Results • Design Decisions • Use Design 1 • Improve Tasks 1 & 2 • Next Steps • Analyze results for Tasks 1 & 2 • Create new Design 1 • Repeat simulation to compare old & new designs • Iterate if necessary UCB HCC Retreat

  35. Research Issues: Navigation Predictions • Develop IR model for predicting link selection • Requirements • Information need (task metadata) • Representation of pages (page metadata) • Method for selecting links (relevance ranking) • Maintaining user’s conceptual model during site traversal (scent [Fur97,LC98,Pir97]) • One possible approach • Information Foraging Theory [PC95,Pir97,PPR96] • Functional categorization of pages based on features • Prediction of relevance to current page • Consider link connectivity, text similarity & usage UCB HCC Retreat

  36. Other HCC-Related Projects • Using a large digital desk in design • Ame Elliot • Using visualization for light design • Dan Glaser • User interfaces and computer security • Prof. Doug Tygar, Rachna Dahmija UCB HCC Retreat

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