• Journal of KIISE:Computer Systems and Theory
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• v.34 no.5_6
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• pp.169-175
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• 2007

Suffix arrays, fundamental full-text index data structures, can be efficiently used where patterns are queried many times. Although many useful full-text index data structures have been proposed, their O(nlogn)-bit space consumption motivates researchers to develop more space-efficient ones. However, their space efficient versions such as the compressed suffix array and the FM-index have been developed; those can not reduce the practical working space because their constructions are based on the existing suffix array. Recently, two direct construction algorithms of compressed suffix arrays from the text without constructing the suffix array have been proposed. In this paper, we compare practical performance of these algorithms of compressed suffix arrays with that of various algorithms of suffix arrays by measuring the construction times, the peak memory usages during construction and the sizes of their final outputs.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.8
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• pp.319-326
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• 2007

To perform fast searching in massive data such as DNA strings, the most efficient method is to construct full-text index data structures of given strings. The widely used full-text index structures are suffix trees and suffix arrays. Since the suffix may uses less space than the suffix tree, the suffix array is proper for DNA strings. Previously developed construction algorithms of suffix arrays are not suitable for DNA strings since those are designed for integer alphabets. We propose a fast algorithm to construct suffix arrays on DNA strings whose alphabet sizes are fixed by 4. We reduce the construction time by improving encoding and merging steps on Kim et al.[1]'s algorithm. Experimental results show that our algorithm constructs suffix arrays on DNA strings 1.3-1.6 times faster than Kim et al.'s algorithm, and also for other algorithms in most cases.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04a
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• pp.809-811
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• 2003

써픽스 배열은 써픽스 트리와 더불어 바이오인포매틱스(bioinformatics) 등에 널리 사용되는 전체 텍스트(full-text)의 인덱스 자료구조이다. 여러 응용분야에서 처리해야하는 데이터양의 기하급수적인 증가에 따라, 써픽스 배열을 압축하여 저장해야 하는 필요성이 커지고 있다. Grossi와 Vitter는 주어진 스트링의 써픽스 배열이 있을 경우, 작은 저장 공간을 사용하는 압축된 써픽스 배열(compressed suffix arrays)을 정의하였다. 본 논문에서는 주어진 스트링에서 써픽스 배열을 구축할 필요 없이, 직접적으로 압축된 써픽스 배열을 구축하는 선형시간 알고리즘을 제시한다.

• The Transactions of the Korea Information Processing Society
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• v.7 no.2
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• pp.411-425
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• 2000

Information retrieval systems for structured documents which are written in SGML or XML support partial retrieval of document. In order to efficiently process queries based on document structures, low memory overhead for indexing, quick response time for queries, supports to powerful types of user queries, and minimal updates of index structure for document updates are required. This paper suggests the Global Document Instance Tree(GDIT) and proposes an effective indexing scheme and query processing algorithms based on the GDIT. The indexing scheme keeps up indexing and retrieval effciency and also guarantees minimal updates of the index structure when document structures are updated.