• Journal of KIISE
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• v.43 no.10
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• pp.1073-1078
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• 2016

(${\delta}$, ${\gamma}$)-matching for strings over integer alphabets can be applied to such fields as musical melody and share prices on stock markets. In this paper, we define ${\delta}$-approximate periods and ${\gamma}$-approximate periods of strings over integer alphabets. We also present two $O(n^2)$-time algorithms, each of which finds minimum ${\delta}$-approximate periods and minimum ${\gamma}$-approximate periods, respectively. Then, we provide the experimental results of execution times of both algorithms.

• 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.

• 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.

• Proceedings of the Korea Information Processing Society Conference
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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.

• Journal of KIISE
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• v.44 no.8
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• pp.760-766
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• 2017

Repetitive strings have been studied in diverse fields such as data compression, bioinformatics and so on. Recently, two problems of approximate periods of strings over integer alphabets were introduced, finding minimum ${\delta}-approximate$ periods and finding minimum ${\gamma}-approximate$ periods. Both problems can be solved in $O(n^2)$ time when n is the length of the string. In this paper, we present two parallel algorithms for solving the above two problems in O(n) time using $O(n^2)$ threads, respectively. The experimental results show that our parallel algorithms for finding minimum ${\delta}-approximate$ (resp. ${\gamma}-approximate$) periods run approximately 19.7 (resp. 40.08) times faster than the sequential algorithms when n = 10,000.

• Smart Media Journal
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• v.9 no.2
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• pp.33-38
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• 2020

Order preserving matching refers to the problem of reporting substrings of a given text where there exists order isomorphism with the pattern. In this paper, we propose a new algorithm based on filtering and evaluation. The proposed algorithm is simple and easy to implement, and runs in linear time on average. Experimental results show that it works efficiently with real world data.

• The KIPS Transactions:PartA
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• v.17A no.5
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• pp.221-228
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• 2010

Since string operations were applied to computational biology, security and search for Internet, various data structures and algorithms for computing efficient string operations have been studied. The all-pairs suffix-prefix matching is to find the longest suffix and prefix among given strings. The matching algorithm is importantly used for fast approximation algorithm to find the shortest superstring, as well as for bio-informatics and data compressions. In this paper, we propose an algorithm to find all-pairs suffix-prefix matching using the suffix array, which takes O($k{\cdot}m$)�� time complexity. The suffix array algorithm is proven to be better than the suffix tree algorithm by showing it takes less time and memory through experiments.

• Korean Journal of Construction Engineering and Management
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• v.21 no.6
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• pp.125-134
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• 2020

Natural language encountered in construction documents largely deviates from those that are recommended by the authorities. Such practice that is lacking in coherence will discourage integrated research with automation, and it will hurt the productivity in the industry for the long run. This research aims to compare multiple string similarity (string matching) algorithms to compare each algorithm's performance in recognizing the same task name written in multiple different ways. We also aim to start a debate on how prevalent the aforementioned deviation is. Finally, we composed a small dataset that associates construction task names found in practice with the corresponding task names that are less cluttered w.r.t their formatting. We expect that this dataset can be used to validate future natural language processing approaches.

• 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.