Indexing compressed text

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Practical Entropy-Compressed Rank/Select Dictionary (2006, methodology): “ons or navigations. Various succinct representation techniques have been developed to represent data structures such as ordered sets [25, 19, 20, 21], ordinal trees [1, 26, 5, 6, 13, 18, 23], strings [4, 9, 10, 22, 23, 24], functions [17], and labeled trees [1, 3]. All these data structures are base”
Compressed representations of sequences and full-text indexes (2007, methodology): “For example, in Figure 2 we have that T [3] = s is the tenth character of T bwt and we correctly have T [2] = T bwt [LF(10)] = T bwt [12] = i [Ferragina and Manzini 2005].”
Indexing Compressed Text (2003, methodology): “For a formal proof of the correctness see [8].”
Compressed full-text indexes (2007, methodology): “… are some results achieving O(occ + o(n)) time for large enough m [Grossi and Vitter 2000, 2006], O(occ) time for large enough m [He et al. 2005], and even O(occ) time without any restriction on m, for not very large alphabets, using O(nHk(T) log. n) bits of space [Ferragina and Manzini 2005].”