1 / 4

Interactive Pattern Discovery with Mirage

Interactive Pattern Discovery with Mirage. A fundamental concern in data analysis is to find correlations among different things. Mirage uses exploratory visualization, intuitive graphical operations to help

adrienne-conway
Download Presentation

Interactive Pattern Discovery with Mirage

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Interactive Pattern Discovery with Mirage A fundamental concern in data analysis is to find correlations among different things. Mirage uses exploratory visualization, intuitive graphical operations to help • Track horizontal correlations across different types of attributes for the same objects or events • Track vertical correlations across layers of abstraction from signals to the results of analysis • Integrate human and machine pattern recognition capabilities Lucent Technologies - Proprietary

  2. Vertical Correlations across Layers of Analysis Processed Images Raw Images Numerical Features Classes and Groups Validation in Input Domain Relationship between Groups Interpretation in Context Lucent Technologies - Proprietary

  3. Horizontal Correlations: Similarity of Objects from Different Perspectives • Objects can be described by many types of attributes: position, morphology, color, spectra, temporal variability, motion parameters … • Meaningful similarity metric exists only for attributes of the same type • Similar groups found from one perspective need to be correlated to those from others e.g. Are the objects similar in color also similar in shape? Shape groups Color groups Lucent Technologies - Proprietary

  4. Human / Machine Interaction in Pattern Discovery Domain expertise Hypotheses from theory or intuition Decisions in algorithmic choices Interpretation in context Visualized data geometry Systematic exploration control Computed features & data structures Tentative classifications, indicators Lucent Technologies - Proprietary

More Related