14. information search and visualization. introduction information retrieval, database management ...
Post on 17-Jan-2016
223 Views
Preview:
TRANSCRIPT
14. Information Search and Visualization
Introduction
information retrieval, database management information gathering, seeking, filtering, or visualization
data mining from data warehouses and data marts knowledge networks or semantic webs
information search using traditional UI – hurdle for novice users and an inadequate for experts
Improvements on traditional text and multimedia searching seem possible as a new generation of visualization strategies for query formulation and information presentation emerges
task actions (browsing or searching) represented by interface actions (scrolling, zooming, joining, or linking)
Tasks – specific/extended fact finding, exploration of availability, open-ended browsing and problem analysis
Searching in Textual Documents and Database Querying
search engine SQL – requires training, and even then users make frequent errors natural-language queries – appealing but limited computer processing
capacity form-fillin queries and query-by-example simple and advanced search interfaces (fig. 14.1) five-phase framework
1. Formulation: expressing the search source, fields, phrases, variants
2. Initiation of action: launching the search explicit, implicit initiation, dynamic query
3. Review of results: reading messages and outcomes sequence and cluster
4. Refinement: formulating the next step history buffer5. Use: compiling or disseminating insight
Image search -- query by image content (QBIC) search
for distinctive features or search for distinctive colors
Map search – search by features
Design or diagram search – finding engine designs with
pistons smaller than 6 cm
Sound search – Music-information retrieval system
Video search
Animation search
Multimedia Document Searches
Advanced Filtering and Search Interfaces
filtering with complex Boolean queries - difficulty of use
automatic filtering - user constructed set of keywords to
dynamically generated information
dynamic queries - direct manipulation queries
faceted metadata search - integrating category browsing with
keyword searching
collaborative filtering - each user rates items, and then system
suggest unread items
multilingual searches
visual searches -
Information Visualization
How to present and manipulate large amounts of information in
compact and user-controlled ways
Information visualization - the use of interactive visual
representations of abstract data to amplify cognition
Resistance to visual approach - textual tools use compact
presentations that are rich with meaningful information and
comfortingly familiar
visual-information-seeking mantra – overview first, zoom and
filter, then details on demand
Data type by task taxonomy (TTT) and seven tasks (Box 14.2)
1. 1-D 1inear data in a sequential manner – textual documents, dictionaries, alphabetical list of
names interface-design issues include what fonts, color, size to use, and what
overview, scrolling, or selection methods to provide for users
2. 2-D map data maps, floor plans, newspaper layouts interface-domain features (size, color, opacity) user tasks – to find adjacent items, regions containing items, paths between
items and to perform the seven basic tasks
Information Visualization
3. 3-D world data Computer-assisted medical imaging, architectural drawing, mechanical design,
chemical structure modeling, and scientific simulations users’ tasks typically deal with continuous variables such as temperature or
density cope with the position and orientation when viewing the objects potential
problems of occlusion and navigation overviews, landmarks, teleoperation, multiple views and TUI
4. Multidimensional data n attributes in a n-dimensional space tasks include finding patterns such as, clusters, correlations, gaps and outliers three-dimensional scattergram (disorientation and occlusion)
Information Visualization
5. Temporal data items have a start and finish time, and that items may overlap
finding all events before, after, or during time period and the seven basic tasks
6. Tree data Treemap
7. Network data shortest or least costly paths connecting two items or traversing the entire
network
Information Visualization
8. Overview task zoom-out views of each data type to see the entire collection plus detail view
movable field-of-view box (zoom factors of 3 to 30), fisheye strategy
9. Zoom task to control zoom focus and zoom factor
10.Filter task sliders, buttons, or other control widgets coupled with rapid display update
Information Visualization
11.Details-on-demand task simply click on an item to get a pop-up window with values of each of the
attributes
12.Relate task proximity, containment, connection, color coding; highlighting
13.History task
history of actions to support undo, replay, and progressive refinement
14.Extract task extract , save, send by electronic mail, insert, publish
Information Visualization
14.Challenges for information visualization import data
combine visual representations with textual labels
see related information
view large volumes of data
integrate data mining
collaborate with others
achieve universal usability
Information Visualization
top related