FP-Krishna

From CS294-10 Visualization Sp11

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(Initial Problem Presentation)
(Description - Idea I)
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Krishna Janakiraman
Krishna Janakiraman
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== Description - Idea I ==
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== Description - Exploring time series through visual queries ==
Existing time series exploration techniques enable exploration via zooming the axes, drawing query contours, via techniques such as generalized selection, by bounding boxes and by building augmented suffix trees. However, these techniques do not seem to show the existence of recurring patterns at varying resolutions within the time series.  
Existing time series exploration techniques enable exploration via zooming the axes, drawing query contours, via techniques such as generalized selection, by bounding boxes and by building augmented suffix trees. However, these techniques do not seem to show the existence of recurring patterns at varying resolutions within the time series.  

Revision as of 16:45, 6 April 2011

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Group Members

Krishna Janakiraman

Description - Exploring time series through visual queries

Existing time series exploration techniques enable exploration via zooming the axes, drawing query contours, via techniques such as generalized selection, by bounding boxes and by building augmented suffix trees. However, these techniques do not seem to show the existence of recurring patterns at varying resolutions within the time series.

For example, a given 'U' or a downward slope shaped query pattern could be present in the time series in a stretched form and can be composed of smaller similarly shaped patterns. As another example, suppose a user wants to identify a sequence of events in a time series, the matching pattern could be a contiguous sequence of events or sequence of events interspersed with other unrelated events. At a higher resolution, certain classes of the latter pattern could be relevant for the user.

The main research questions I would like to investigate are: how can patterns {shapes, sequences and conditions} be expressed and identified across varying resolutions in a time series, how such patterns can be both relaxed and constrained to allow greater flexibility and finally how the results can be summarized and visualized.

Description - Idea II

Traditional approaches towards querying and exploring knowledge representations (or) ontology instances have been through building question answering systems or through using sophisticated query languages such as SPARQL. While the latter is almost impossible to learn for non-technical users, the former is incredibly hard to implement. In addition, interfaces built using either of these approaches typically give 'point answers' and do not depict the rich network between subjects, objects and predicates while showing the results. For my final project, I will be developing a visual query language to explore a knowledge representation. Users can build sophisticated queries by drawing 'query graphs'. The result is displayed as a graph too, and the layout is determined by the query. Users can use generalized selection and brushing to prune the results and update the queries.

Initial Problem Presentation

I will be proceeding with Idea II

Link to slides: File:Krishna-initial-preso.pdf

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