The KIPS Transactions:PartD (정보처리학회논문지D)

Korea Information Processing Society (한국정보처리학회)
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An Unsupervised Clustering Technique of XML Documents based on Function Transform and FFT

함수 변환과 FFT에 기반한 조정자가 없는 XML 문서 클러스터링 기법

  • 이호석 (호서대학교 공과대학 뉴미디어학과)
  • Published : 2007.04.30
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Abstract

This paper discusses a new unsupervised XML document clustering technique based on the function transform and FFT(Fast Fourier Transform). An XML document is transformed into a discrete function based on the hierarchical nesting structure of the elements. The discrete function is, then, transformed into vectors using FFT. The vectors of two documents are compared using a weighted Euclidean distance metric. If the comparison is lower than the pre specified threshold, the two documents are considered similar in the structure and are grouped into the same cluster. XML clustering can be useful for the storage and searching of XML documents. The experiments were conducted with 800 synthetic documents and also with 520 real documents. The experiments showed that the function transform and FFT are effective for the incremental and unsupervised clustering of XML documents similar in structure.

본 논문은 함수 변환(Function Transform)과 FFT(Fast Fourier Transform)를 사용하는 새로운 XML 문서 클리스터링 기법에 대하여 논한다. 본 문서 클러스터링 기법은 조정자 없이 점진적으로 수행된다. XML 문서는 엘리먼트의 계층적인 구조에 기반하여 이산 함수로 변환된다. 이산 함수는 FFT를 사용하여 벡터로 변환된다. 문서를 나타내는 벡터는 가중치 유클리디안 거리 메트릭을 사용하여 비교된다. 비교 결과가 미리 정의된 값보다 작을 때에는 비교되는 두 개의 문서는 구조적으로 비슷한 것으로 간주되어 동일한 그룹으로 분류된다. XML 문서 클리스터링은 XML 문서의 저장과 검색에 유용하게 사용될 수 있다. 800개의 합서 문서와 520개의 실제 문서를 사용하여 실험하였다. 실험 결과는 함수변환과 FFT는 XML 문서를 엘리먼트의 구조를 기반으로 하여 점진적으로 조정자 없이 효과적으로 분류하는 것을 보여주었다.

Keywords

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