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Erschienen in:
2010 | OriginalPaper | Buchkapitel
Compressed Self-indices Supporting Conjunctive Queries on Document Collections
verfasst von : Diego Arroyuelo, Senén González, Mauricio Oyarzún
Erschienen in: String Processing and Information Retrieval
Verlag: Springer Berlin Heidelberg
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We prove that a document collection, represented as a unique sequence
T
of
n
terms over a vocabulary Σ, can be represented in
nH
0
(
T
) +
o
(
n
)(
H
0
(
T
) + 1) bits of space, such that a conjunctive query
t
1
∧ ⋯ ∧
t
k
can be answered in
O
(
kδ
loglog|Σ|) adaptive time, where
δ
is the instance difficulty of the query, as defined by Barbay and Kenyon in their SODA’02 paper, and
H
0
(
T
) is the empirical entropy of order 0 of
T
. As a comparison, using an inverted index plus the adaptive intersection algorithm by Barbay and Kenyon takes
$O(k\delta\log{\frac{n_M}{\delta}})$
, where
n
M
is the length of the shortest and longest occurrence lists, respectively, among those of the query terms. Thus, we can replace an inverted index by a more space-efficient in-memory encoding, outperforming the query performance of inverted indices when the ratio
$\frac{n_M}{\delta}$
is
ω
(log|Σ|).