2016
Journal article  Restricted

Space-Efficient Substring Occurrence Estimation

Orlandi A., Venturini R.

Text indexing  Compressed full-text indexing  Computer Science Applications  Full-text indexing  Full text Index  General Computer Science  Data structures  Applied Mathematics  Pattern matching 

In this paper we study the problem of estimating the number of occurrences of substrings in textual data: A text on some alphabet of length is preprocessed and an index is built. The index is used in lieu of the text to answer queries of the form , returning an approximated number of the occurrences of an arbitrary pattern as a substring of . The problem has its main application in selectivity estimation related to the LIKE predicate in textual databases. Our focus is on obtaining an algorithmic solution with guaranteed error rates and small footprint. To achieve that, we first enrich previous work in the area of compressed text-indexing providing an optimal data structure that, for a given additive error , requires bits. We also approach the issue of guaranteeing exact answers for sufficiently frequent patterns, providing a data structure whose size scales with the amount of such patterns. Our theoretical findings are supported by experiments showing the practical impact of our data structures.

Source: Algorithmica 74 (2016): 65–90. doi:10.1007/s00453-014-9936-y

Publisher: Springer Science + Business Media, New York , Stati Uniti d'America


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BibTeX entry
@article{oai:it.cnr:prodotti:366887,
	title = {Space-Efficient Substring Occurrence Estimation},
	author = {Orlandi A. and Venturini R.},
	publisher = {Springer Science + Business Media, New York , Stati Uniti d'America},
	doi = {10.1007/s00453-014-9936-y and 10.1145/1989284.1989300},
	journal = {Algorithmica},
	volume = {74},
	pages = {65–90},
	year = {2016}
}