Research questions about… tag clouds?

Tag clouds are graphical representations of attributes and their relative importance. In a recent paper, we have argued that tag clouds might help bridge the gap between collaboration and Business Intelligence.

Here are some fun things to do with tag clouds:

  • In our paper, a tag cloud computation is the equivalent of an approximate orthogonal top-k range query. There has been little work in this area. We propose error measures for this problem. Our own approach is based on the pre-computation of icebergs.
  • Unlike bar charts, a tag cloud can have 50, 100 or 150 attributes. It makes it easier to collaborate because you do not need so often to rely on hierarchies. However, tag clouds tend to mix badly with non-nominal dimensions such as time or price. More generally, more work is needed on multidimensional tag clouds.
  • The problem of optimally drawing tag clouds is still very much open.

2 thoughts on “Research questions about… tag clouds?”

  1. I like the article: Straightforward approach to an interesting problem.

    I think that deserves some sort of generalization. Is there a core difference between tags and semi-structured schema? Are not roll, dice and other operations relevant to a wider range of “soft” marking methods, rather than tags?

  2. I like the article: Straightforward approach to an interesting problem.

    Thanks.

    I think that deserves some sort of generalization. Is there a core difference between tags and semi-structured schema? Are not roll, dice and other operations relevant to a wider range of “soft” marking methods, rather than tags?

    It does deserve a generalization and I think that the paper hints to it but tag clouds offer something concrete to think about.

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