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CS3041 – Final week

CS3041 – Final week. Today: Searching and Visualization Friday: Software tools Study guide distributed (in class only) Monday: Social Imps Study guide review Tuesday: Final Exam Thursday: UI in Games (optional) Final project due. Chapter 14. Information Searching and Visualization.

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CS3041 – Final week

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  1. CS3041 – Final week • Today: Searching and Visualization • Friday: Software tools • Study guide distributed (in class only) • Monday: Social Imps • Study guide review • Tuesday: Final Exam • Thursday: UI in Games (optional) • Final project due

  2. Chapter 14 Information Searching and Visualization

  3. Searching • Many Forms of Information Search • Searching text and database • Multimedia documents • Data Visualization • Different levels of searching • Specific fact finding • Extended fact finding • Information availability • Open-ended browsing

  4. Searching Text and Databases • Simple case, general keyword search • Google, Yahoo, Lycos • Users often have problems with high volumes of returned data • SQL • Powerful tool for data mining 'experts‘ • Natural language queries • Ask Jeeves • Form-fillin queries

  5. Five Phase Fact Finding Framework • Formulation • Identify data source, search criteria • Initiation of action • Explicit (button) or implicit (immediate) • Review of results • Typically a results overview • Refinement • Adjust keywords / criteria, drill down • Usage • Export results for later use / sharing

  6. Multimedia Documents • Much harder problem than text • Often relies on metadata • Automatic recognition requires many auxiliary technologies (image processing, speech to text) • Some common search types • Images (KimDaBa) • Maps (Mapquest) • Design / diagram (AutoCAD) • Sound • Video • Animations (Disney internal animation tools)

  7. Example: KimDaBa • "KimDaBa or KDE Image Database is a tool which you can use to easily sort your images.“ • Keyword / metadata browser

  8. Example: KimDaBa • Search criteria Visual browsing

  9. Filtering and Search Interfaces • Filtering with complex Boolean queries • Users often trip here because of the difference between natural language vs boolean algebra • "List all employees who live in Boston and New York“ • In language, AND = inclusion • In boolean logic, AND = refinement • "I'll eat pepperoni or sausage pizza“ • In language, OR = exclusion • Boolean, OR = inclusion

  10. Filtering and Search Interfaces • Automatic filtering • Applying user-constructed criteria to dynamic information • Spam filters

  11. Filtering and Search Interfaces • Dynamic queries • Adjusting interface controls via direct manipulation and displaying the results immediately ( < 100 ms) • Facilitates data exploration • Collaborative filtering • Users rate results • Tivo uses this ("Thumbs up" vs "Thumbs down") • Multilingual searches • Visual searches

  12. Filtering and Search Interfaces • Dynamic searching • Spotfire visualization tool

  13. Filtering and Search Interfaces • Visual searches • Airplane seat selection

  14. Information and Data Visualization • Visualization is an area of research that aims to let users visually explore large data sets, looking for patterns and relationships • A picture is worth 1K words • An interface is worth 1K pictures • Visual data mining • People are good at visual pattern matching • Visual information seeking mantra: • Overview first, zoom and filter, then details on demand (times7)

  15. Information and Data Visualization • Data types by task taxonomy • 1D Linear • text, sequences • 2D Map • geographic, blueprints • 3D World • Medical, CAD/CAM • Multidimensional • Temporal • Tree • Network

  16. Information and Data Visualization • Multidimensional Data • Any data set with n attributes, where n > 3 • N-d tools need to support a wide variety of tasks • Finding patterns • Identifying correlations, clusters, gaps, outliers • Lots of different techniques • Scatterplots • Glyphs • Dimensional stacking (  Jeff’s thesis  ) • (1pt extra credit on the final if you find the title) • Parallel coordinates

  17. Information and Data Visualization • Parallel coordinates example • XmdvTool from WPI

  18. Information and Data Visualization • Data visualization tasks • Overview: Gain an overview of the entire collection • Zoom: Zoom in on items of interest • Filter: Filter out uninteresting items • Details on demand: Select an item or group and get details when needed • Relate: View relationships among items • History: Keep a history of actions • Extract: Allow extraction of subcollections and of the query parameters

  19. Information and Data Visualization • Challenges for information visualization tools: • Standardized data import • Combining visual representations with text • Viewing related information • Viewing large volumes of data • Support data mining • Collaboration • Universal usability

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