• Journal of the Korea Society of Computer and Information
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• v.17 no.10
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• pp.107-116
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• 2012

The applying of semantic technologies that aim to let computers understand and automatically process the meaning of the interlinked data on the Web is spreading. In Semantic Web, understanding and accessing the associations between data that is, the meaning between data as well as accessing to the data itself is important. W3C recommended RDF (Resource Description Framework) as a standard format to represent both Semantic Web data and their associations and also proposed several RDF query languages in order to support query processing for RDF data. However further researches on the query language definition considering the semantic associations and query processing techniques are still required. In this paper, using the suffix array-based indexing scheme previously introduced for RDF query processing, we propose a query processing approach to handle ${\rho}$-path query which is the representative type of semantic associations. To evaluate the query processing performance of the proposed approach, we implemented two different types of query processing approaches and measured the average query processing times. The experiments show that the proposed approach achieved 1.8 to 2.5 and 3.8 to 11 times better performance respectively than others two.

• Journal of the Korea Society of Computer and Information
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• v.16 no.7
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• pp.95-103
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• 2011

The actual utilization of Semantic Web technology which aims to provide more intelligent and automated service for information retrieval over the Web becomes gradually reality. RDF is widely used as the one of standard formats to present and manage the voluminous data on the Web. Efficient query processing on RDF data, therefore, is one of the ongoing research topics. Retrieving resources having a specific association from a given resource is the typical query processing type and several researches for this have done. However the most of previous researches have not fully considered discovering the complex relationship among resources such as returning the association between resources as the query processing result. This paper introduces the indexing and query processing for ${\rho}$-intersect operation which is one of the semantic association retrieval types. It includes an indexing scheme using suffix array and optimal processing approaches for handling ${\rho}$-intersect operation. The experimental evaluations shows that the average execution times for the proposed approach is 3~7 times faster than the previous approach.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.3_4
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• pp.145-151
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• 2004

We present an efficient data structure to obtain the range minima in an away in constant time. Recently, suffix ways are extensively used to search DNA sequences fast in bioinformatics. In constructing suffix arrays, solving the range minima problem is necessary When we construct suffix arrays, we should solve the range minima problem not only in a time-efficient way but also in a space-efficient way. The reason is that DNA sequences consist of millions or billions of bases. Until now, the most efficient data structure to find the range minima in an way in constant time is based on the method that converts the range minima problem in an array into the LCA (Lowest Common Ancestor) problem in a Cartesian tree and then converts the LCA problem into the range minima problem in a specific array. This data structure occupies O( n) space and is constructed in O(n) time. However since this data structure includes intermediate data structures required to convert the range minima problem in an array into other problems, it requires large space (=13n) and much time. Our data structure is based on the method that directly solves the range minima problem. Thus, our data structure requires small space (=5n) and less time in practice. As a matter of course, our data structure requires O(n) time and space theoretically.

• Journal of Creative Information Culture
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• v.7 no.3
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• pp.157-165
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• 2021

As the use of various application services utilizing Web and IoT and the need for large amounts of data management expand accordingly, the importance of efficient data expression and exchange scheme and data query processing is increasing. JSON, characterized by its simplicity, is being used in various fields as a format for data exchange and data storage instead of XML, which is a standard data expression and exchange language on the Web. This means that it is important to develop indexing and query processing techniques to effectively access and search large amounts of data expressed in JSON. Therefore, in this paper, we modeled JSON data with a hierarchical structure in a tree form, and proposed indexing and query processing using the path concept. In particular, we designed an index structure using a suffix array widely used in text search and introduced simple and complex path-based JSON data query processing methods.

• Proceedings of the Korean Information Science Society Conference
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• 2005.11a
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• pp.955-957
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• 2005

대용량의 텍스트에 대해 빠른 패턴 검색의 필요성이 증가함에 따라 써픽스 트리, 써픽스 배열 등의 인덱스 자료구조에 대해 다양한 연구들이 진행되었다. 또한 써픽스 배열을 대용량의 인덱스 자료구조로 사용하기 위해 저장 공간을 O(n log n) 비트 이하로 줄이는 문제에 대한 연구들도 많이 수행되었다. 이들 중 Grossi & Vitter 는 써픽스 배열을 압축하여, 기존의 써픽스 배열보다 작은 저장 공간을 사용할 수 있는 알고리즘을 제안하였다. Grossi & Vitter 알고리즘은 압축된 써픽스 배열에서 실제 써픽스 배열의 정보를 찾기 위하여, succinct 표현에서 기본적으로 사용되는 rank와 select 함수를 필요로 한다. 본 논문은 다양한 rank와 select 알고리즘을 각각 사용하는 압축된 써픽스 배열들의 성능 비교를 통해, succinct 표현의 효율적인 구현이 압축된 써픽스 배열의 성능에 미치는 영향을 실험적으로 보인다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2011.01a
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• pp.285-288
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• 2011

시맨틱 웹상에서 메타 데이터를 표현하는 RDF 데이터에 대한 질의 처리를 위해 여러 가지 RDF 질의어가 제안되었으나 리소스간의 복잡한 관계성들의 발견(discovery)을 위한 충분한 지원을 하지 못하고 있다. 본 논문에서는 시맨틱 연관성 검색 유형의 하나인 ${\rho}$-intersect 연산의 처리 방법을 소개한다. 이를 위해 접미사 배열을 이용한 인덱싱과 ${\rho}$-intersect 연산의 특징을 고려한 최적화 방법을 활용한다. 제안된 처리 기법을 통해 전형적인 RDF 질의 유형뿐만 아니라 시맨틱 연관성 질의 유형도 지원할 수 있도록 한다.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10a
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• pp.496-498
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• 2003

접미사 배열은 긴 문자열에 대해 효율적인 문자열 검색을 가능하게 하는 자료구조이다. 접미사 배열은 문자열의 접미사들의 사전식 정렬순서를 배열로 저장한다. 비슷한 효과를 가진 접미사 트리에 비해서 접미사 배열은 저장 공간을 적게 차지하기 때문에 생명정보과학의 염기 서열 등 큰 크기의 문자열의 처리에 더욱 유리하다. 본 논문에서는 2003년에 발표된 Ko-Aluru, K$\square$rkk$\square$inen-Sanders 및 기존의 Manber-Myers 등 세 개의 접미사 배열 생성 알고리즘들의 염기 서열 입력 자료에 대한 실행 시간 및 기억 장치 사용량을 실험을 통해 비교한다. 특히 Ko-Aluru와 K$\square$rkk$\square$inen-Sanders 알고리즘은 실행 시간 및 저장 공간의 이론적인 복잡도가 O(n)으로 동일하기 때문에 실험을 통해서 계산 복잡도에 숨어있는 상수를 비교한다. 실험 결과 K$\square$rkk$\square$inen-Sanders 알고리즘이 가장 효율적임을 보인다.