TagsTreeMaps

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TagsTreeMaps

TagsTreeMapsTM
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TagsTreeMapsTM
The invention solves one of the fundamental problems I had (and I suppose more people like myself using tagging systems extensively): when trying to browse through a large space of tagged information, it is very hard to get a hold on a large number of tags used. Currently used solutions like tag clouds present static approach to present and differentiate presented tags. Eventually, user has problems when trying to find appropriate tags to browse the information. Very often the tags cannot be filtered by any means and they are always represented as a flat structure. My invention not only allows to clearly mark the most important (commonly used) tags, but also delivers plugginable architecture for:
  1. filtering of tags - current plugins are: min/max usage, filtering by tag's name with WordNet meaning extension;
  2. preprocessing tags - current plugins: clustering tags based on
    1. predefined bundles of tags;
    2. string similarity distances;
  3. postprocessing treemap -“ current plugin allows to colour tags so that they are distinctive and much easier to read.

The current prototype allows to perform zoom in/out actions (multi-level) to a selected group of tags, clusters, bundles. Zooming and extensive filtering operations are not delivered by any widely used tagging system I am aware off. Additionally, user can choose between union mode (at least one of the tags in the selected view should be used in the information filtered) or conjunctive mode (all tags must be used) - as opposed to current solutions where only conjunctive mode is delivered. The UI layer of the prototype is build in DHTML/AJAX technology to be easily applied to any currently existing web systems, with features like expand/retract and drag&resize of the treemaps component. Please refer to http://labs.corrib.org/ttm/screencast.htm for screencast movie presenting all features of the component.


                       
                       
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TagsTreeMap Ideas

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Corrib cluster project is supported by Enterprise Ireland under Grant No. ILP/05/203, Science Foundation Ireland under Grant No. SFI/02/CE1/I131.
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