• Journal of KIISE:Computer Systems and Theory
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• v.37 no.2
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• pp.103-109
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• 2010

The edit distance problem is finding the minimum number of edit operations to transform a string into another one. It is one of the important problems in algorithm research and there are some algorithms that compute an optimal edit distance for the one-dimensional languages such as the English alphabet. However, there are a few researches to find the edit distance for the more complicated language such as the Korean or Chinese alphabet. In this paper, we define the measure of the edit distance for the Korean alphabet and present an algorithm for the edit distance problem for the Korean alphabet.

• Journal of KIISE:Computer Systems and Theory
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• v.37 no.6
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• pp.323-329
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• 2010

The edit distance problem is finding the minimum number of edit operations to transform a string into another one. It is one of the important problems in algorithm research and there are some algorithms that compute an optimal edit distance for the one-dimensional languages such as the English alphabet. However, there are a few researches to find the edit distance for the more complicated language such as the Korean or Chinese alphabet. In this paper, we define the measure of the edit distance for the Korean alphabet with the phoneme classification system to improve the previous edit distance algorithm and present an algorithm for the edit distance problem for the Korean alphabet.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06a
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• pp.391-393
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• 2012

반복적인 문자열에 대한 연구는 압축알고리즘이나 모티프검출, 염기서열 분석 등 다양한 분야와 관련되어 연구되고 있다. 반복문자열 연구 중에서도 어느 정도의 불일치를 허용하는 근사반복문자열 연구가 활발히 이루어지고 있다. 본 논문에서는 길이가 각각 m과 n인 문자열 p와 x가 주어졌을 때, p의 x에 대한 거리합기반 근사주기에 대해 정의하고 최소 주기거리를 찾는 문제를 제시한다. 그리고 가중편집거리를 사용했을 때 O($mn^2$)시간, 편집거리를 사용했을 때 O(mn)시간, 해밍거리를 사용했을 때 O(n)시간에 문제를 해결하는 알고리즘을 제시한다.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.1
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• pp.16-21
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• 2002

Repetitive strings have been studied in such diverse fields as molecular biology data compression etc. Some important regularities that have been studied are perods, covers seeds and squares. A natural extension of the repetition problems is to allow errors. Among the four notions above aproximate squares and approximate periodes have been studied. In this paper, we introduce the notion of approximate covers which is an approximate version of covers. Given two strings P(｜P｜=m) and T(｜T｜=n) we propose and algorithm with finds the minimum distance t such that P is a t-approximate cover of T. The algorithm take O(m,n) time for the edit distance and $O(mn^2)$ time of finding a string which is an approximate cover of T is minimum distance is NP-complete.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.2
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• pp.67-74
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• 2013

Approximate string matching problems have been studied in diverse fields. Recently, fast approximate string matching algorithms are being used to reduce the time and costs for the next generation sequencing. To measure the amounts of errors between two strings, we use a distance function such as the edit distance. Given two strings X(|X| = m) and Y(|Y| = n) over an alphabet ${\Sigma}$, the edit distance between X and Y is the minimum number of edit operations to convert X into Y. The edit distance between X and Y can be computed using the well-known dynamic programming technique in O(mn) time and space. The edit distance also can be computed using the Four-Russians' algorithm whose preprocessing step runs in $O((3{\mid}{\Sigma}{\mid})^{2t}t^2)$ time and $O((3{\mid}{\Sigma}{\mid})^{2t}t)$ space and the computation step runs in O(mn/t) time and O(mn) space where t represents the size of the block. In this paper, we present a parallelized version of the computation step of the Four-Russians' algorithm. Our algorithm computes the edit distance between X and Y in O(m+n) time using m/t threads. Then we implemented both the sequential version and our parallelized version of the Four-Russians' algorithm using CUDA to compare the execution times. When t = 1 and t = 2, our algorithm runs about 10 times and 3 times faster than the sequential algorithm, respectively.

• Annual Conference of KIPS
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• 2014.11a
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• pp.62-65
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• 2014

근사문자열매칭 알고리즘은 검색엔진, 컴퓨터보안, 생물정보학 등 많은 분야에서 연구되고 있다. 근사문자열매칭에서는 거리함수를 이용하여 오차를 측정한다. 거리함수로는 해밍거리, 편집거리, 확장편집거리 등이 있다. 이때 확장편집거리는 mn) 시간과 공간에 계산할 수 있으며, 최근 m개의 쓰레드를 이용하여 O(m+n) 시간과 O(mn) 공간을 이용한 병렬알고리즘이 제시되었다. 본 논문에서는 기존의 확장편집거리를 계산하는 병렬알고리즘을 개선한 효율적인 병렬알고리즘을 제시한다. 기존의 병렬알고리즘을 최적화하고, 기존의 병렬알고리즘, 전역메모리만 사용한 최적화된 병렬알고리즘, 공유메모리를 활용한 최적화된 병렬알고리즘의 수행시간을 비교한다. 실험 결과, 개선된 병렬알고리즘이 기존의 병렬알고리즘보다 전처리단계에서 16 ~ 63배 이상, 모든 단계에 대해 19 ~ 24배 이상 빠른 수행시간을 보였다.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.2
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• pp.119-122
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• 2013

Repetitive strings such as periods have been studied vigorously in so diverse fields as data compression, computer-assisted music analysis, bioinformatics, and etc. In bioinformatics, periods are highly related to repetitive patterns in DNA sequences so called tandem repeats. In some cases, quite similar but not the same patterns are repeated and thus we need approximate string matching algorithms to study tandem repeats in DNA sequences. In this paper, we propose a new definition of approximate periods of strings based on distance sum. Given two strings $p({\mid}p{\mid}=m)$ and $x({\mid}x{\mid}=n)$, we propose an algorithm that computes the minimum approximate period distance based on distance sum. Our algorithm runs in $O(mn^2)$ time for the weighted edit distance, and runs in O(mn) time for the edit distance, and runs in O(n) time for the Hamming distance.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.7
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• pp.213-218
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• 2015

Given two strings X and Y (|X|=m, |Y|=n) over an alphabet ${\Sigma}$, the extended edit distance between X and Y can be computed using dynamic programming in O(mn) time and space. Recently, a parallel algorithm that takes O(m+n) time and O(mn) space using m threads to compute the extended edit distance between X and Y was presented. In this paper, we present an improved parallel algorithm using the shared memory on GPU. The experimental results show that our parallel algorithm runs about 19~25 times faster than the previous parallel algorithm.

• Annual Conference of KIPS
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• 2012.04a
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• pp.261-264
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• 2012

상수 크기의 알파벳 ${\Sigma}$에 대해 길이가 각각 m, n인 두 문자열 X와 Y의 편집거리는 X를 Y로 변환하기 위해 필요한 최소 편집연산의 수로 정의된다. 두 문자열의 편집거리는 잘 알려진 동적프로그래밍을 이용하여 O(mn) 시간과 공간에 계산할 수 있으며, 4-러시안 알고리즘을 이용해도 계산할 수 있다. 4-러시안 알고리즘은 블록 크기를 상수 t라 할 때, 전처리 단계에서 $O\((3{\mid}{\Sigma}{\mid})^{2t}t^2\)$ 시간과 $O\((3{\mid}{\Sigma}{\mid})^{2t}t^2\)$ 공간이 필요하며, 계산 단계에서 O(mn/t) 시간과 O(mn) 공간을 이용하여 편집거리를 계산하는 알고리즘이다. 본 논문에서는 4-러시안 알고리즘의 계산 단계를 CUDA를 이용하여 구현하고 실험을 통해 CPU 기반의 순차적인 수행시간과 GPU 기반의 병렬적인 수행시간의 비교결과를 제시한다. 본 논문의 병렬알고리즘은 m/t개의 쓰레드를 사용하여 O(m+n) 시간에 편집거리를 계산한다. GPU 기반의 알고리즘이 CPU 기반의 알고리즘 보다 t=1일 때 약 10배 빠르고, t=2일 때 약 3배 빠른 결과를 보였다.

• The Journal of the Korea Contents Association
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• v.11 no.12
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• pp.12-18
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• 2011

Most smartphone use virtual keypads based on touch-pad. The virtual keypads often make typographical errors because of the physical limitations of device such as small screen and limited input methods. To resolve this problem, many similar word-finding methods have been studied. In the paper, we propose an edit distance method (a well-known string similarity measure) that is modified to consider various types of virtual keypads. The proposed method effectively covers typographical errors in various keypads by converting an input string into a physical key sequence and by reflecting characteristics of virtual keypads to edit scores. In the experiments with various keypads, the proposed method showed better performances than a typical edit distance method.