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- W2765525826 abstract "A significant problem in computer science is the management of large data strings and a great number of works dealing with the specific problem has been published in the scientific literature. In this article, we use a technique to store efficiently biological sequences, making use of data structures like suffix trees and inverted files and also employing techniques like n-grams, in order to improve previous constructions. In our attempt, we drastically reduce the space needed to store the inverted indexes, by representing the substrings that appear more frequently in a more compact inverted index. Our technique is based on n-gram indexing, providing us the extra advantage of indexing sequences that cannot be separated in words. Moreover, our technique combines classical one level with two-level n-gram inverted file indexing. Our results suggest that the new proposed algorithm can compress the data more efficiently than previous attempts." @default.
- W2765525826 created "2017-11-10" @default.
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- W2765525826 date "2017-01-01" @default.
- W2765525826 modified "2023-10-17" @default.
- W2765525826 title "Space Efficient Data Structures for N-gram Retrieval" @default.
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- W2765525826 doi "https://doi.org/10.3934/medsci.2017.4.426" @default.
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