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- W1844008849 abstract "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(kδloglog|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(kdeltalog{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|)." @default.
- W1844008849 created "2016-06-24" @default.
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- W1844008849 date "2010-01-01" @default.
- W1844008849 modified "2023-10-14" @default.
- W1844008849 title "Compressed Self-indices Supporting Conjunctive Queries on Document Collections" @default.
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- W1844008849 doi "https://doi.org/10.1007/978-3-642-16321-0_5" @default.
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