Given a sequence S = s1s2..sn of integers smaller than r = O(polylog(n)), we show how S can be represented using n H_0(S) + o(n) bits, so that we can know any character at position q, as well as answer rank and select queries on S, in constant time. H_0(S) is the zero-order empirical entropy of S and n H_0(S) provides an information-theoretic lower bound to the bit storage of any sequence S via a fixed encoding of its symbols. This extends previous results on binary sequences, and improves previous results on general sequences where those queries are answered in O(log r) time. For larger r, we can still represent S in n H_0(S) + o(n log r) bits and answer queries in O(log r/log log n) time. Another contribution of this article is to show how to combine our compressed representation of integer sequences with a compression boosting technique to design compressed full-text indexes that scale well with the size of the input alphabet Sigma. Specifically, we design a variant of the FM-index that indexes a string T[1, n] within n H_k(T) + o(n) bits of storage, where H_k(T) is the kth-order empirical entropy of T. This space bound holds simultaneously for all k <= alpha log_{Sigma} n, constant 0 < alpha < 1, and |Sigma| = O(polylog(n)). This index counts the occurrences of an arbitrary pattern P[1, p] as a substring of T in O(p) time; it locates each pattern occurrence in O(log^{1+eps} n) time for any constant 0 < eps < 1; and reports a text substring of length L in O(L + log^{1+eps} n) time. Compared to all previous works, our index is the first that removes the alphabet-size dependance from all query times, in particular, counting time is linear in the pattern length. Still, our index uses essentially the same space of the kth-order entropy of the text T, which is the best space obtained in previous work. We can also handle larger alphabets of size |Sigma| = O(n^{beta}), for any 0 < beta < 1, by paying o(n log|Sigma|) extra space and multiplying all query times by O(log |Sigma|/log log n).
Compressed Representations of sequences and full-text indexes
FERRAGINA, PAOLO;G. MANZINI;
2007-01-01
Abstract
Given a sequence S = s1s2..sn of integers smaller than r = O(polylog(n)), we show how S can be represented using n H_0(S) + o(n) bits, so that we can know any character at position q, as well as answer rank and select queries on S, in constant time. H_0(S) is the zero-order empirical entropy of S and n H_0(S) provides an information-theoretic lower bound to the bit storage of any sequence S via a fixed encoding of its symbols. This extends previous results on binary sequences, and improves previous results on general sequences where those queries are answered in O(log r) time. For larger r, we can still represent S in n H_0(S) + o(n log r) bits and answer queries in O(log r/log log n) time. Another contribution of this article is to show how to combine our compressed representation of integer sequences with a compression boosting technique to design compressed full-text indexes that scale well with the size of the input alphabet Sigma. Specifically, we design a variant of the FM-index that indexes a string T[1, n] within n H_k(T) + o(n) bits of storage, where H_k(T) is the kth-order empirical entropy of T. This space bound holds simultaneously for all k <= alpha log_{Sigma} n, constant 0 < alpha < 1, and |Sigma| = O(polylog(n)). This index counts the occurrences of an arbitrary pattern P[1, p] as a substring of T in O(p) time; it locates each pattern occurrence in O(log^{1+eps} n) time for any constant 0 < eps < 1; and reports a text substring of length L in O(L + log^{1+eps} n) time. Compared to all previous works, our index is the first that removes the alphabet-size dependance from all query times, in particular, counting time is linear in the pattern length. Still, our index uses essentially the same space of the kth-order entropy of the text T, which is the best space obtained in previous work. We can also handle larger alphabets of size |Sigma| = O(n^{beta}), for any 0 < beta < 1, by paying o(n log|Sigma|) extra space and multiplying all query times by O(log |Sigma|/log log n).I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
