• 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.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.6 s.312
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• pp.43-51
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• 2006

This paper proposes a metrics for example matching under the example-based machine translation for English-Korean machine translation. Our metrics served as similarity measure is based on edit-distance algorithm, and it is employed to retrieve the most similar example sentences to a given query. Basically it makes use of simple information such as lemma and part-of-speech information of typographically mismatched words. Edit-distance algorithm cannot fully reflect the context of matched word units. In other words, only if matched word units are ordered, it is considered that the contribution of full matching context to similarity is identical to that of partial matching context for the sequence of words in which mismatching word units are intervened. To overcome this drawback, we propose the context-weighting scheme that uses the contiguity information of matched word units to catch the full context. To change the edit-distance metrics representing dissimilarity to similarity metrics, to apply this context-weighted metrics to the example matching problem and also to rank by similarity, we normalize it. In addition, we generalize previous methods using some linguistic information to one representative system. In order to verify the correctness of the proposed context-weighted metrics, we carry out the experiment to compare it with generalized previous methods.

• Journal of the Korea Society of Computer and Information
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• v.20 no.10
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• pp.99-105
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• 2015

The growth of internet infrastructure and a tremendous increment of internet users lead actively to found internet newspaper publishing companies, which are able to dig up and publish own news articles. In disregard of these quantitative growth of internet newspaper companies, the qualitative growth of them doesn't coincide with the quantitative growth. Therefore, to require social responsibility and to build healthy media environment, Korean government has put in force registration system of internet newspaper company. According to this system, internet newspaper companies have to produce at the inside over 30 percent of weekly publications, and this requisite increases the needs of its verification. This paper investigates technologies to measure the self-supplied news volumes of internet newspaper company, examines validity of them, and presents appropriate method to measure. To compare huge amount of news articles rapidly, the presented method is based on the modified edit-distance, which reflects human cognition of word and empirical information related with it. To prove correctness of our presented method, we show experimental results for some real internet news articles.

• 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.

• Proceedings of the Korean Society of Computer Information Conference
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• 2011.01a
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• pp.249-252
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• 2011

본 논문에서는 쇼크(shock) 그래프 기반의 뼈대 특징을 이용하여 모양 정보를 분류하기 위해 그래프 편집 거리(edit cost) 기반의 k-means 군집화 알고리즘을 적용하는 방법을 제안한다. 본 논문에서 제안된 방법에서는 먼저 질의 영상과 대상 데이터베이스 영상으로부터 뼈대 기반의 쇼크 그래프를 추출한 후 종점(end points)과 분기점(branch points)을 가중치를 이용하여 적응적으로 선택한다. 그런 다음, 두 영상 사이의 편집 거리를 구하여 이를 k-means 군집화 알고리즘의 거리 척도로 적용함으로써 대용량의 영상을 보다 효과적으로 분류한다. 성능을 평가하기 위해서 제안된 알고리즘을 MPEG-7 데이터베이스에 적용하였으며, 그 결과 제안된 영상 분류 방법이 기존의 영상 분류 방법에 비해서 보다 효과적으로 모양 기반의 영상을 분류하였음을 확인하였다.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.109-118
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• 2022

Workers' anomalous trajectories allow us to detect emergency situations in the workplace, such as accidents of workers, security threats, and fire. In this work, we develop a scheme to detect abnormal trajectories of workers using the edit distance on real sequence (EDR) and density method. Our anomaly detection scheme consists of two phases: offline phase and online phase. In the offline phase, we design a method to determine the algorithm parameters: distance threshold and density threshold using accumulated trajectories. In the online phase, an input trajectory is detected as normal or abnormal. To achieve this objective, neighbor density of the input trajectory is calculated using the distance threshold. Then, the input trajectory is marked as an anomaly if its density is less than the density threshold. We also evaluate performance of the proposed scheme based on the MIT Badge dataset in this work. The experimental results show that over 80 % of anomalous trajectories are detected with a precision of about 70 %, and F1-score achieves 74.68 %.

• Journal of IKEEE
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• v.12 no.4
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• pp.217-224
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• 2008

This paper provides a framework for semantic correspondence of heterogeneous databases using self- organizing map. It solves the problem of overlapping between different databases due to their different schemas. Clustering technique using self-organizing maps (SOM) is tested and evaluated to assess its performance when using different kinds of data. Preprocessing of database is performed prior to clustering using edit distance algorithm, principal component analysis (PCA), and normalization function to identify the features necessary for clustering.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06a
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• pp.31-33
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• 2006

활자유전학(typogenetics)은 인공생명(artificial life) 연구에 사용되는 형식 시스템으로서, 자가복제자와 하이퍼사이클의 출현에 관한 연구에 효과적인 모델이다. 본 연구에서는 하이퍼사이클에 추가될 복제자의 차이점과 유사점을 측정하기 위하여 편집거리(edit distance)를 사용하여, 기존의 연구에서 생성된 하이퍼사이클 보다 더 큰 크기의 다양한 하이퍼사이클들을 생성하였다.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06c
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• pp.58-60
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• 2006

근래에 XML 문서가 인터넷에서 정보 교환의 방법으로 표준화됨에 따라, 많은 양의 데이터가 XML 문서 포맷으로 저장되고 있다. XML 문서의 유사성 연구는 크게 edit-distance를 이용하는 방법, 문서의 그래프 모델을 이용하는 방법, 문서의 매트릭스 모델을 이용하는 방법 등이 있다. 최근에는 문서를 encoding 하고 푸리에 변환을 이용하는 방법이 보고되었다. 본 논문에서는 XML 문서를 함수로 변환하여 모델링하여 문서의 구조적 유사성을 비교하는 방법을 제안한다. 제안된 방법을 사용하여 XML 문서를 함수로 모델링하였으며 XML 문서 간의 유사성을 비교해 보았다.

• Asia pacific journal of information systems
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• v.18 no.1
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• pp.79-96
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• 2008

One of the roles of the Semantic Web services is to execute dynamic intra-organizational services including the integration and interoperation of business processes. Since different organizations design their processes differently, the retrieval of similar semantic business processes is necessary in order to support inter-organizational collaborations. Most approaches for finding services that have certain features and support certain business processes have relied on some type of logical reasoning and exact matching. This paper presents our approach of using imprecise matching for expanding results from an exact matching engine to query the OWL(Web Ontology Language) MIT Process Handbook. MIT Process Handbook is an electronic repository of best-practice business processes. The Handbook is intended to help people: (1) redesigning organizational processes, (2) inventing new processes, and (3) sharing ideas about organizational practices. In order to use the MIT Process Handbook for process retrieval experiments, we had to export it into an OWL-based format. We model the Process Handbook meta-model in OWL and export the processes in the Handbook as instances of the meta-model. Next, we need to find a sizable number of queries and their corresponding correct answers in the Process Handbook. Many previous studies devised artificial dataset composed of randomly generated numbers without real meaning and used subjective ratings for correct answers and similarity values between processes. To generate a semantic-preserving test data set, we create 20 variants for each target process that are syntactically different but semantically equivalent using mutation operators. These variants represent the correct answers of the target process. We devise diverse similarity algorithms based on values of process attributes and structures of business processes. We use simple similarity algorithms for text retrieval such as TF-IDF and Levenshtein edit distance to devise our approaches, and utilize tree edit distance measure because semantic processes are appeared to have a graph structure. Also, we design similarity algorithms considering similarity of process structure such as part process, goal, and exception. Since we can identify relationships between semantic process and its subcomponents, this information can be utilized for calculating similarities between processes. Dice's coefficient and Jaccard similarity measures are utilized to calculate portion of overlaps between processes in diverse ways. We perform retrieval experiments to compare the performance of the devised similarity algorithms. We measure the retrieval performance in terms of precision, recall and F measure? the harmonic mean of precision and recall. The tree edit distance shows the poorest performance in terms of all measures. TF-IDF and the method incorporating TF-IDF measure and Levenshtein edit distance show better performances than other devised methods. These two measures are focused on similarity between name and descriptions of process. In addition, we calculate rank correlation coefficient, Kendall's tau b, between the number of process mutations and ranking of similarity values among the mutation sets. In this experiment, similarity measures based on process structure, such as Dice's, Jaccard, and derivatives of these measures, show greater coefficient than measures based on values of process attributes. However, the Lev-TFIDF-JaccardAll measure considering process structure and attributes' values together shows reasonably better performances in these two experiments. For retrieving semantic process, we can think that it's better to consider diverse aspects of process similarity such as process structure and values of process attributes. We generate semantic process data and its dataset for retrieval experiment from MIT Process Handbook repository. We suggest imprecise query algorithms that expand retrieval results from exact matching engine such as SPARQL, and compare the retrieval performances of the similarity algorithms. For the limitations and future work, we need to perform experiments with other dataset from other domain. And, since there are many similarity values from diverse measures, we may find better ways to identify relevant processes by applying these values simultaneously.