46,837 research outputs found
Error-tolerant Finite State Recognition with Applications to Morphological Analysis and Spelling Correction
Error-tolerant recognition enables the recognition of strings that deviate
mildly from any string in the regular set recognized by the underlying finite
state recognizer. Such recognition has applications in error-tolerant
morphological processing, spelling correction, and approximate string matching
in information retrieval. After a description of the concepts and algorithms
involved, we give examples from two applications: In the context of
morphological analysis, error-tolerant recognition allows misspelled input word
forms to be corrected, and morphologically analyzed concurrently. We present an
application of this to error-tolerant analysis of agglutinative morphology of
Turkish words. The algorithm can be applied to morphological analysis of any
language whose morphology is fully captured by a single (and possibly very
large) finite state transducer, regardless of the word formation processes and
morphographemic phenomena involved. In the context of spelling correction,
error-tolerant recognition can be used to enumerate correct candidate forms
from a given misspelled string within a certain edit distance. Again, it can be
applied to any language with a word list comprising all inflected forms, or
whose morphology is fully described by a finite state transducer. We present
experimental results for spelling correction for a number of languages. These
results indicate that such recognition works very efficiently for candidate
generation in spelling correction for many European languages such as English,
Dutch, French, German, Italian (and others) with very large word lists of root
and inflected forms (some containing well over 200,000 forms), generating all
candidate solutions within 10 to 45 milliseconds (with edit distance 1) on a
SparcStation 10/41. For spelling correction in Turkish, error-tolerantComment: Replaces 9504031. gzipped, uuencoded postscript file. To appear in
Computational Linguistics Volume 22 No:1, 1996, Also available as
ftp://ftp.cs.bilkent.edu.tr/pub/ko/clpaper9512.ps.
Pattern Matching and Consensus Problems on Weighted Sequences and Profiles
We study pattern matching problems on two major representations of uncertain
sequences used in molecular biology: weighted sequences (also known as position
weight matrices, PWM) and profiles (i.e., scoring matrices). In the simple
version, in which only the pattern or only the text is uncertain, we obtain
efficient algorithms with theoretically-provable running times using a
variation of the lookahead scoring technique. We also consider a general
variant of the pattern matching problems in which both the pattern and the text
are uncertain. Central to our solution is a special case where the sequences
have equal length, called the consensus problem. We propose algorithms for the
consensus problem parameterized by the number of strings that match one of the
sequences. As our basic approach, a careful adaptation of the classic
meet-in-the-middle algorithm for the knapsack problem is used. On the lower
bound side, we prove that our dependence on the parameter is optimal up to
lower-order terms conditioned on the optimality of the original algorithm for
the knapsack problem.Comment: 22 page
Covering Problems for Partial Words and for Indeterminate Strings
We consider the problem of computing a shortest solid cover of an
indeterminate string. An indeterminate string may contain non-solid symbols,
each of which specifies a subset of the alphabet that could be present at the
corresponding position. We also consider covering partial words, which are a
special case of indeterminate strings where each non-solid symbol is a don't
care symbol. We prove that indeterminate string covering problem and partial
word covering problem are NP-complete for binary alphabet and show that both
problems are fixed-parameter tractable with respect to , the number of
non-solid symbols. For the indeterminate string covering problem we obtain a
-time algorithm. For the partial word covering
problem we obtain a -time algorithm. We
prove that, unless the Exponential Time Hypothesis is false, no
-time solution exists for either problem, which shows
that our algorithm for this case is close to optimal. We also present an
algorithm for both problems which is feasible in practice.Comment: full version (simplified and corrected); preliminary version appeared
at ISAAC 2014; 14 pages, 4 figure
String Matching with Variable Length Gaps
We consider string matching with variable length gaps. Given a string and
a pattern consisting of strings separated by variable length gaps
(arbitrary strings of length in a specified range), the problem is to find all
ending positions of substrings in that match . This problem is a basic
primitive in computational biology applications. Let and be the lengths
of and , respectively, and let be the number of strings in . We
present a new algorithm achieving time and space , where is the sum of the lower bounds of the lengths of the gaps in
and is the total number of occurrences of the strings in
within . Compared to the previous results this bound essentially achieves
the best known time and space complexities simultaneously. Consequently, our
algorithm obtains the best known bounds for almost all combinations of ,
, , , and . Our algorithm is surprisingly simple and
straightforward to implement. We also present algorithms for finding and
encoding the positions of all strings in for every match of the pattern.Comment: draft of full version, extended abstract at SPIRE 201
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