• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.6D
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• pp.849-856
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• 2011

This paper proposes a method for transforming unstructured text contents of engineering documents, which have complex hierarchical structure of subtitles with various heading symbols, into a semi-structured XML document according to the hierarchical subtitle structure. In order to extract the hierarchical structure from plain text information, this study employed a method of document structure extraction which is an analysis technique of the document structure. In addition, a method for processing enumerative text contents was developed to increase overall accuracy during extraction of the subtitles and construction of a hierarchical subtitle structure. An application module was developed based on the proposed method, and the performance of the module was evaluated with 40 test documents containing structural calculation records of bridges. The first test group of 20 documents related to the superstructure of steel girder bridges as applied in a previous study and they were used to verify the enhanced performance of the proposed method. The test results show that the new module guarantees an increase in accuracy and reliability in comparison with the test results of the previous study. The remaining 20 test documents were used to evaluate the applicability of the method. The final mean value of accuracy exceeded 99%, and the standard deviation was 1.52. The final results demonstrate that the proposed method can be applied to diverse heading symbols in various types of engineering documents to represent the hierarchical subtitle structure in a semi-structured XML document.

• 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.

• Journal of KIISE:Software and Applications
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• v.29 no.6
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• pp.367-376
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• 2002

XML allows users to define elements using arbitrary words and organize them in a nested structure. These features of XML offer both challenges and opportunities in information retrieval and document management. In this paper, we propose a new methodology for computing similarity considering XML semantics - meanings of the elements and nested structures of XML documents. We generate extended-element vectors, using thesaurus, to normalize synonyms, compound words, and abbreviations and build similarity matrix using them. And then we compute similarity between XML elements. We also discover and minimize XML structure using automata(NFA(Nondeterministic Finite Automata) and DFA(Deterministic Finite automata). We compute similarity between XML structures using similarity matrix between elements and minimized XML structures. Our methodology considering XML semantics shows 100% accuracy in identifying the category of real documents from on-line bookstore.

• The KIPS Transactions:PartD
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• v.9D no.2
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• pp.297-306
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• 2002

This paper handles the design and implementation of the system for transforming the XML document bated on XML Schema being different in syntax but similar in logic, with using structured differences analysis. In the system, the merge data is generated from the source and destination documents by utilizing data registry and structured differences analysis, and then XML document is generated from the generated merge data. The XML document transformation system is designed that transformation process to the present application system from the different application system gains advantage in the aspect of time, cost, and reliability. The implementation environment of the system is that it is run on IBM compatible PC and it is developed using the software of visual basic 6.0 with the Platform of Windows 2000.

• The KIPS Transactions:PartB
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• v.17B no.2
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• pp.125-138
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• 2010

The purpose of this research is to enhance document recognition system which is essential for developing full-text retrieval system of the document image data stored in the digital library of a public institution. To achieve this purpose, the main tasks of this research are: 1) analyzing the document image data and then developing its image preprocessing technology and document structure analysis one, 2) building its specialized knowledge base consisting of document layout and property, character model and word dictionary, respectively. In addition, developing the management tool of this knowledge base, the document recognition system is able to handle the various types of the document image data. Currently, we developed the prototype system of document recognition which is combined with the specialized knowledge base and the library of document structure analysis, respectively, adapted for the document image data housed in National Archives of Korea. With the results of this research, we plan to build up the test-bed and estimate the performance of document recognition system to maximize the utilization of full-text retrieval system.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06b
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• pp.562-567
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• 2008

XML은 W3C 표준으로 채택된 이후로 많은 어플리케이션에서 데이터를 표현하는 방법으로 사용되고 있다. XML문서는 특정 어플리케이션에 종속적이기 때문에 XSLT를 이용하여 변환한 뒤 사용하게 된다. 그러나 변환에는 많은 노력, 시간과 비용이 소요되기 때문에 이를 자동으로 변환하는 시스템을 구축하는 것이 최선의 방법이다. 이를 위해서 XTGen이나 XSLT 스크립트 시스템이 기존에 제안되었지만 사용자가 엘리먼트간의 관계를 수동으로 처리하는 방식이거나 변환 문서간 단말 노드의 1:1 매칭이라는 제약과 대규모 변환에 어려움이 있다. 본 논문은 JAWS를 이용한 엘리먼트간의 의미 관계 분석과 DTD의 구조를 분석하여 XSLT를 생성함으로써 기존 시스템들의 단점을 보완하고 더 높은 정확성을 보장한다는 장점을 가지고 있다. 본 논문에서 제안하는 시스템은 XML 문서를 변환하기 위한 XSLT를 자동으로 생성하여 XML 문서를 변환하는 모든 과정을 자동화 함으로써 문서 변환에 따르는 비용의 절감할 수 있을 것으로 기대된다.

• Annual Conference on Human and Language Technology
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• 2023.10a
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• pp.125-130
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• 2023

최근 심층 신경망을 활용한 한국어 자연어 처리에 대한 관심이 높아지고 있지만, 한국어 자연어 처리에 적합한 신경망 구조 탐색에 대한 연구는 이뤄지지 않았다. 본 논문에서는 문서 분류 정확도를 보상으로 하는 강화 학습 알고리즘을 이용하여 장단기 기억 신경망으로 한국어 문서 분류에 적합한 심층 신경망 구조를 탐색하였으며, 탐색을 위해 사전 학습한 한국어 임베딩 성능과 탐색한 신경망 구조를 분석하였다. 탐색을 통해 찾아낸 신경망 구조는 기존 한국어 자연어 처리 모델에 대해 4 가지 한국어 문서 분류 과제로 비교하였을 때 일반적으로 성능이 우수하고 모델의 크기가 작아 효율적이었다.

• Proceedings of the Korea Multimedia Society Conference
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• 2002.11b
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• pp.190-193
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• 2002

인터넷의 급속한 보급과 함께 멀티미디어 문서의 사용에 대한 사용자의 요구가 증가하고 이에 따라 멀티미디어 문서 정보 검색에 관련된 연구들이 국내외적으로 활발하게 진행되고 있다. 멀티미디어 문서는, 데이터의 양이 방대할 뿐 아니라 데이터가 비정형화되어 있기 때문에 분석이 복잡하며 또한 효율적으로 저장, 검색하기가 매우 어렵다. 그러므로 이를 위해서는 적절한 멀티미디어 자료 저장 구조를 지닌 정보 검색 시스템이 절실히 요구된다. 따라서 본 논문에서는 대용량 멀티미디어 문서에 적합한 저장 구조를 가진 정보검색 시스템을 제안한다.

• Journal of Korea Multimedia Society
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• v.7 no.5
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• pp.601-616
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• 2004

Information retrieval systems for structured documents provide multiple levels of retrieval capability by supporting structure-based queries. In order to process structure-based queries for structured documents, information for structural nesting relationship between elements and for element sequence must be maintained. This paper presents four index structures that can process various query types about structures such as structural relationships between elements or element occurrence order. The proposed algorithms are based on the concept of Global Document Instance Tree.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.2
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• pp.205-211
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• 2012

The retrieved documents have to be transformed into proper data structure for the clustering algorithms of statistics and machine learning. A popular data structure for document clustering is document-term matrix. This matrix has the occurred frequency value of a term in each document. There is a sparsity problem in this matrix because most frequencies of the matrix are 0 values. This problem affects the clustering performance. The sparseness of document-term matrix decreases the performance of clustering result. So, this research uses the factor score by factor analysis to solve the sparsity problem in document clustering. The document-term matrix is transformed to document-factor score matrix using factor scores in this paper. Also, the document-factor score matrix is used as input data for document clustering. To compare the clustering performances between document-term matrix and document-factor score matrix, this research applies two typed matrices to self organizing map (SOM) clustering.