Efficient tree-structured categorical retrieval
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We study a document retrieval problem in the new framework where D text documents are organized in a category tree with a pre-defined number h of categories. This situation occurs e.g. with taxomonic trees in biology or subject classification systems for scientific literature. Given a string pattern p and a category (level in the category tree), we wish to efficiently retrieve the t categorical units containing this pattern and belonging to the category. We propose several efficient solutions for this problem. One of them uses n(logσ(1+o(1))+log D+O(h)) + O(Δ) bits of space and O(|p|+t) query time, where n is the total length of the documents, σ the size of the alphabet used in the documents and Δ is the total number of nodes in the category tree. Another solution uses n(logσ(1+o(1))+O(log D))+O(Δ)+O(Dlog n) bits of space and O(|p|+tlog D) query time. We finally propose other solutions which are more space-efficient at the expense of a slight increase in query time.
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