Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Lightweight Fingerprints for Fast Approximate Keyword Matching Using
  Bitwise Operations   We aim to speed up approximate keyword matching by storing a lightweight,
fixed-size block of data for each string, called a fingerprint. These work in a
similar way to hash values; however, they can be also used for matching with
errors. They store information regarding symbol occurrences using individual
bits, and they can be compared against each other with a constant number of
bitwise operations. In this way, certain strings can be deduced to be at least
within the distance $k$ from each other (using Hamming or Levenshtein distance)
without performing an explicit verification. We show experimentally that for a
preprocessed collection of strings, fingerprints can provide substantial
speedups for $k = 1$, namely over $2.5$ times for the Hamming distance and over
$10$ times for the Levenshtein distance. Tests were conducted on synthetic and
real-world English and URL data.

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The categories of this paper are: funct-an
6
The categories of this paper are: astro-ph
37
The categories of this paper are: supr-con
18
The categories of this paper are: econ
19
The categories of this paper are: eess
0
The categories of this paper are: hep-ph
12
The categories of this paper are: nucl-th
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The categories of this paper are: atom-ph
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The categories of this paper are: mtrl-th
36
The categories of this paper are: cmp-lg
9
The categories of this paper are: nlin
20
The categories of this paper are: acc-phys
33
The categories of this paper are: plasm-ph
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The categories of this paper are: dg-ga
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The categories of this paper are: alg-geom
2
The categories of this paper are: math