• Journal of KIISE:Databases
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• v.31 no.3
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• pp.331-339
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• 2004

XML has got to be a new standard for data representation and exchanging by its many good points, and the core part of many new researches and emerging technologies. However, the self-describing characteristic, which is one of XML's good points, caused the spreading of XML documents with different structures, and so the need of the research for the effective XML-document search has been proposed. This paper is for the analysis of the problem in BitCube, which is a bitmap indexing that shows high performance grounded on its fast retrieval. In addition, to resolve the problem of BitCube, we did design and implement xPlaneb(XML Plane Web) which it a new 3-dimensional bitmap indexing made of linked lists. We propose an effective information retrieval technique by replacing BitCube operations with new ones and reconstructing 3-dimensional array index of BitCube with effective nodes. Performance evaluation shows that the proposed technique is better than BitCube, as the amount of document increases, in terms of memory consumptions and operation speed.

• Journal of the Korean Society for information Management
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• v.24 no.1 s.63
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• pp.209-226
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• 2007

XML documents format on the Web provides a mechanism to impose their content and logical structure information. Therefore, an XML processor provides access to their content and structure. The purpose of this study is to investigate the usefulness of structural hints in the leaf node language model-based XML document retrieval. In order to this purpose, this experiment tested the performances of the leaf node language model-based XML retrieval system to compare the queries for a topic containing only content-only constraints and both content constrains and structure constraints. A newly designed and implemented leaf node language model-based XML retrieval system was used. And we participated in the ad-hoc track of INEX 2005 and conducted an experiment using a large-scale XML test collection provided by INEX 2005.

• Journal of Digital Contents Society
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• v.11 no.3
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• pp.357-365
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• 2010

Personalized web search engine provides personalized results to users by query expansion, re-ranking or other methods representing user's intention. The personalized result page includes URL, page title and small text fragment of each web document. which is known as snippet. The snippet is the summary of the document which includes the keywords issued by either user or search engine itself. Users can verify the relevancy of the whole document using only the snippet, easily. The document summary (snippet) is an important information which makes users determine whether or not to click the link to the whole document. Hence, if a search engine generates personalized document summaries, it can provide a more satisfactory search results to users. In this paper, we propose a personalized document summary system for personalized web search engines. The proposed system provides increased degree of satisfaction to users with marginal overhead.

• Journal of KIISE:Software and Applications
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• v.26 no.10
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• pp.1204-1218
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• 1999

문서영상 검색을 위한 디지털도서관의 대부분은 논문제목과/또는 논문요약으로부터 만들어진 색인에 근거한 제한적인 검색기능을 제공하고 있다. 본 논문에서는 영문 문서영상전체에 대한 검색을 위한 단어 영상 형태 특징기반의 단어검색시스템을 제안한다. 본 논문에서는 검색의 효율성과 정확도를 높이기 위해 1) 기존의 단어검색시스템에서 사용된 특징들을 조합하여 사용하며, 2) 특징의 개수 및 위치뿐만 아니라 특징들의 순서를 포함하여 매칭하는 방법을 사용하며, 3) 특징비교에 의해 검색결과를 얻은 후에 여과목적으로 문자인식을 부분적으로 적용하는 2단계의 검색방법을 사용한다. 제안된 시스템의 동작은 다음과 같다. 문서 영상이 주어지면, 문서 영상 구조가 분석되고 단어 영역들의 조합으로 분할된다. 단어 영상의 특징들이 추출되어 저장된다. 사용자의 텍스트 질의가 주어지면 이에 대응되는 단어 영상이 만들어지며 이로부터 영상특징이 추출된다. 이 참조 특징과 저장된 특징들과 비교하여 유사한 단어를 검색하게 된다. 제안된 시스템은 IBM-PC를 이용한 웹 환경에서 구축되었으며, 영문 문서영상을 이용하여 실험이 수행되었다. 실험결과는 본 논문에서 제안하는 방법들의 유효성을 보여주고 있다. Abstract Most existing digital libraries for document image retrieval provide a limited retrieval service due to their indexing from document titles and/or the content of document abstracts. This paper proposes a word spotting system for full English document image retrieval based on word image shape features. In order to improve not only the efficiency but also the precision of a retrieval system, we develop the system by 1) using a combination of the holistic features which have been used in the existing word spotting systems, 2) performing image matching by comparing the order of features in a word in addition to the number of features and their positions, and 3) adopting 2 stage retrieval strategies by obtaining retrieval results by image feature matching and applying OCR(Optical Charater Recognition) partly to the results for filtering purpose. The proposed system operates as follows: given a document image, its structure is analyzed and is segmented into a set of word regions. Then, word shape features are extracted and stored. Given a user's query with text, features are extracted after its corresponding word image is generated. This reference model is compared with the stored features to find out similar words. The proposed system is implemented with IBM-PC in a web environment and its experiments are performed with English document images. Experimental results show the effectiveness of the proposed methods.

• Journal of KIISE:Databases
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• v.34 no.3
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• pp.206-216
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• 2007

With respect to the Semantic Web proposed to overcome the limitation of the Web, OWL has been recommended as the ontology language used to give a well-defined meaning to diverse data. OWL is the representative ontology language suggested by W3C. An efficient retrieval of OWL data requires a well-constructed storage schema. In this paper, we propose a storage schema construction technique which supports more efficient query processing. A retrieval technique corresponding to the proposed storage schema is also introduced. OWL data includes inheritance information of classes and properties. When OWL data is extracted, hierarchy information should be considered. For this reason, an additional XML document is created to preserve hierarchy information and stored in an XML database system. An existing numbering scheme is utilized to extract ancestor/descendent relationships, and order information of nodes is added as attribute values of elements in an XML document. Thus, it is possible to retrieve subclasses and subproperties fast and easily. The improved query performance from experiments shows the effectiveness of the proposed storage schema construction and retrieval method.

• The KIPS Transactions:PartD
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• v.11D no.7 s.96
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• pp.1357-1366
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• 2004

As the importance or XML is increasing to manage information and exchange data efficiently in the web, there are on going works about structural integration and retrieval. The XML. document with the defined structure can retrieve the structure through the DTD or XML schema, but the existing method can't apply to XML. documents which haven't the structure information. Therefore. in this paper we propose a new clus-tering technique at a basic research which make it possible to retrieve structure fast about the XML documents that haven't the structure information. We first estract the feature of frequent structure from each XML document. And we cluster based on the similar structure by con-sidering the frequent structure as representative structure of the XML document, which makes it possible to retrieve the XML document raster than dealing with the whole documents that have different structure. And also we perform the structure retrieval about XML documents based on the clusters which is the group of similar structure. Moreover, we show efficiency of proposed method to describe how to apply the structure retrieval as well as to display the example of application result.

• International Journal of Internet, Broadcasting and Communication
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• v.4 no.1
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• pp.13-17
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• 2012

Indexing allows converting raw document collection into easily searchable representation. Web searching by Google or Yahoo provides subsecond response time which is made possible by efficient indexing of web-pages over the entire Web. Indexing process gets challenging when the scale gets bigger. Parallel techniques, such as MapReduce framework can assist in efficient large-scale indexing process. In this paper we propose PDFindexer, system for indexing scientific papers in PDF using MapReduce programming model. Unlike Web search engines, our target domain is scientific papers, which has pre-defined structure, such as title, abstract, sections, references. Our proposed system enables parsing scientific papers in PDF recreating their structure and performing efficient distributed indexing with MapReduce framework in a cluster of nodes. We provide the overview of the system, their components and interactions among them. We discuss some issues related with the design of the system and usage of MapReduce in parsing and indexing of large document collection.

• Journal of the Korean Society for information Management
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• v.23 no.3 s.61
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• pp.5-21
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• 2006

In recent years, theories of image and sound analysis have been proposed to work with text retrieval systems and have progressed quickly with the rapid progress in data processing speeds. This study proposes a common representation format for multimedia documents (CRFMD) composed of both images and text to form a single data structure. It also shows that image classification of a given test set is dramatically improved when text features are encoded together with image features. CRFMD might be applicable to other areas of multimedia document retrieval and processing, such as medical image retrieval, World Wide Web searching, and museum collection retrieval.

• Journal of Korea Society of Industrial Information Systems
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• v.13 no.5
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• pp.22-28
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• 2008

This paper aims to offer a solution based on semantic document classification to improve e-Government utilization and efficiency for people using their own information retrieval system and linguistic expression. Generally, semantic document classification method is an approach that classifies documents based on the diverse relationships between keywords in a document without fully describing hierarchial concepts between keywords. Our approach considers the deep meanings within the context of the document and radically enhances the information retrieval performance. Concept Weight Document Classification(CoWDC) method, which goes beyond using existing keyword and simple thesaurus/ontology methods by fully considering the concept hierarchy of various concepts is proposed, experimented, and evaluated. With the recognition that in order to verify the superiority of the semantic retrieval technology through test results of the CoWDC and efficiently integrate it into the e-Government, creation of a thesaurus, management of the operating system, expansion of the knowledge base and improvements in search service and accuracy at the national level were needed.

• The Journal of Society for e-Business Studies
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• v.9 no.1
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• pp.21-38
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• 2004

With its recent popularity, Web is now considered as a huge repository of information. Most documents on the web have been created using HTML(Hyper Text Markup Language). Even though HTML is simple and easy to learn, it has several features that are obstacles to the efficient information retrieval. XML(eXtensible Markup Language) can provide a solution to such problems and in fact, has already been used in many applications, XML is a standard markup language for exchanging data on the web. It can describe a document structure freely by defining its DTD, which enables efficient integration and retrieval of data on the web. In this paper, we propose a versatile and efficient XML document manager. Its features include (i) form-based XML editor that enables easy creation of new XML documents, (ii) automatic document converter that can transform HTML documents with similar structure into XML documents automatically, and (iii) GUI-based DTD editor.