노드정보를 이용한 문서검색의 성능에 관한 연구
A Study on the Performance of Stuructured Document Retrieval using Node Information
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초록
노드는 문서를 구성하는 작은 크기의 의미있는 정보 단위이다. 정보검색에 문서의 구조정보를 이용함과 더불어 문서보다 작은 검색단위에 대한 연구가 활발히 이루어지고 있다. 이 연구에서는 노드정보를 이용한 검색실험을 위해 벡터공간모델 검색기법을 사용하여 다양한 유사도 산출방식을 적용한 실험과 구조정보를 활용한 확장 실험을 수행하였다. 실험결과 문서의 유사도를 산출하는 방식에 따른 검색성능의 차이는 거의 나타나지 않았으며, 구조정보를 적용하는 확장 노드검색이 가장 좋은 성능을 나타냈다.
Abstract
Node is the semantic unit and a part of structured document. Information retrieval from structured documents offers an opportunity to go subdivided below the document level in search of relevant information, making any element in an structured document a retrievable unit. The node-based document retrieval constitutes several similarity calculating methods and the extended node retrieval method using structure information. Retrieval performance is hardly influenced by the methods for determining document similarity. The extended node method outperformed the others as a whole.
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