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Apart from the best current solution to the problem, we obtain several byproducts of independent interest applicable to partial sums, text indexes, suffix arrays, the Burrows–Wheeler transform, and others.
Unfortunately, those "general-purpose" text indexes are not a good choice for a collection of genomes of individuals of the same species.
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Text indexing may be supplemented by other syntactic techniques so as to increase its precision or robustness.
Advances in computer storage, telecommunications, software for computer sharing, and automated techniques of text indexing and searching fueled the development of an on-line database service industry.
It includes a basic full text index for fast searching.
These textual segments are indexed with a text indexing tool accessible in the retrieval interface.
Because many videos contain spoken texts, text recognition can be applied to extract text, which then can be indexed using methods designed for automatic text indexing.
Different from our leveraged full text index, they index a small domain of books as well as screenshots.
The first one, as a text-based search, is expected to perform at the level of the current state-of-the-art text indexing systems.
Our index uses O(n|Σ|logn) extra space on average and with high probability, where n is the length of the text (indexing) or the number of strings to index (dictionary lookup).
For a document with textual content, text indexing can be viewed as the extraction of descriptors (words) which are organized in specialized structures for retrieval.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com