Approximate structural search in trees

As an example, suppose the query is looking for a node labeled A which has a sibling labeled B. Now suppose there is no tree which has this, but there is a tree where a node labeled A has a cousin labeled B. Then I'd like the query to find this tree.

I could find some work computing the similarity between trees, based on a tree-edit distance.

This work has a couple of problems:

• The query is usually a very small tree, whereas the document is a big tree, so the similarity will be small.
• Some queries are not expressible as trees. Consider a query searching for a node labeled A which has either a B-labeled child or a C-labeled grandchild, or both. This disjunction cannot be expressed as a tree.
• It is not clear to me how does the tree-edit distance relate to the idea of relevance to a user. Suppose the system finds t1 and t2 for a query q, but similarity(t1,q) > similarity(t2,q). How do I know that the user will also prefer t1 over t2?

But I'm sure I'm not the first person to think of all this stuff. So, is there some literature?

kai

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