Information Search and Visualization

1. Information Search and Visualization Lecture 11

2. Information Retrieval vs. Database Management • Information Retrieval • Unstructured text • Multimedia data (music, images, etc) • Queries come from examples or freeform text • Database Management • Structured database systems with orderly attributes and sorted keys • Queries rely on values of fields and retrieve records that match CS774 – Spring 2006

3. Task Actions • Browsing and searching facilitated by interface actions • Example tasks • Specific fact finding (known-item search) • Find the email address of Hillary Clinton • Extended fact finding • What other books are by the author of Jurassic Park? • Exploration of availability • Is there new work on voice recognition in the ACM digital library? • Open-ended browsing and problem analysis • Is there new research on fibromyalgia that might help my patient? CS774 – Spring 2006

4. Finding information • Determine where to search • Convert information need into interface actions • Express actions in a a query language or via a series of mouse selections • Finding aids • Table of contents or indexes in books • Hot topics lists • Topic hierarchies CS774 – Spring 2006

5. Internet Searching • Greatly improved when Google introduced the PageRank algorithm to supplement occurrence of terms • Advance search interfaces available • Human-generated directory interface • Query Facilities • Natural-language queries • Boolean queries CS774 – Spring 2006

6. Database Querying • Database Querying • Structured Query Lanuage (SQL) standard for searching relational databases • SELECT Document# FROM Journal-DB WHERE (Date >= 2001 AND Date <= 2003) AND (Language = English or French) AND (Publisher = ASIST OR HFES OR ACM) CS774 – Spring 2006

7. Search Interface • Five-phase framework to clarify user interfaces fro textual search • Formulation: expressing the search • Initiation of action: launching the search • Review of results: reading messages and outcomes • Refinement: formulating the next step • Use: compiling and disseminating insight CS774 – Spring 2006

8. Question • Should textual search interfaces should keep details of how the search is performed hidden from the users. Decide which approach will allow the user to get more accurate results. CS774 – Spring 2006

9. Multimedia Document Searches • Early stages of development • Use textual descriptions or metadata searches • Examples • Image search • Map search • Design or diagram search • Sound Search • Video Search • Animation Search CS774 – Spring 2006

10. Advanced Filtering • Filtering with complex Boolean queries • Available from some IR systems, but difficulty to use inhibits widespread adoption • Difference between informal English interpretation and logical interpretation • Interfaces have used Venn diagrams, decision tables, and metaphors of water flowing through filters • Automatic filtering • User constructs set of criteria and documents that meet that criteria are flagged as they come into the system CS774 – Spring 2006

11. Advanced Search Interfaces • Dynamic Queries • Direct-manipulation Queries • Sliders and buttons provide query manipulation • Requires use of rapid, incremental, and reversible actions with immediate display feedback • less than 100 milliseconds • Provides overview of data CS774 – Spring 2006

12. Advanced Search Interfaces (cont.) • Faceted metadata search • Integrates category browsing with keyword search From Flamenco Fine Arts Search CS774 – Spring 2006

13. Advanced Search Interfaces (cont.) • Multilingual searches • Also known as cross-lingual searches • Enter a search in one language and retrieve documents in another language • Visual searches • Use visual representation of possible field values • Example: selecting locations from a map to find relevant tourist information CS774 – Spring 2006

14. Information Visualization • Use of interactive visual representations of abstract data to amplify cognition • Abstract characteristic distinguished information visualization from scientific visualization • User interfaces manipulate large numbers of items (102-106) • Humans good at visual interpretation • Detect changes in size, color, shape, movement, or texture • Field is too immature to have guidelines, principles, and theories CS774 – Spring 2006

15. Data Types • 1D Linear • Data organized in a sequential manner • Ex: Color coding by time of last modification • 2D map data • Task-domain attributes and interface-domain features • 3D world data • Tasks typically deal with continuous variables • Results presented as volumes or surfaces CS774 – Spring 2006

16. Data Types (cont.) • Multidimensional data • n attributes in n-dimensional space • Visualizations • Dynamic 2 dimension scatter plot • Clustering algorithms • Temporal data • Focus on events that begin and end at particular times CS774 – Spring 2006

17. Data Types (cont.) • Tree data • Collections of items in which each item has a link to one parent item • Represents include indentation or node-and-link diagram • Network data • Items are linked to an arbitrary number of other items CS774 – Spring 2006

18. Tasks • Overview Task • Zoom out to see entire collection • Zoom Task • Zoom in on some portion of the collection • Filter Task • Remove uninteresting items • Details-on-demand Task CS774 – Spring 2006

19. Task (cont.) • Relate Task • Show relationships by proximity, by containment, connected lines, or color coding • History Task • Supports undo, replay, and progressive refinement • Extract Task • Save, send, or insert into a statistical or presentation package the set of found items CS774 – Spring 2006

20. Question • What do think are the challenges first-time users face when using an information-exploration system? Propose how these challenges can be overcome. CS774 – Spring 2006