• Journal of KIISE:Databases
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• v.32 no.6
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• pp.650-661
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• 2005

As the Internet is growing, the use of XML which is a standard of semi-structured document is increasing. Therefore, there are on going works about integration and retrieval of XML documents. However, the basis of efficient integration and retrieval of documents is to cluster XML documents with similar structure. The conventional XML clustering approaches use the hierarchical clustering algorithm that produces the demanded number of clusters through repeated merge, but it have some problems that it is difficult to compute the similarity between XML documents and it costs much time to compare similarity repeatedly. In order to address this problem, we use clustering algorithm for transactional data that is scale for large size of data. In this paper we use common structures from XML documents that don't have DTD or schema. In order to use common structures of XML document, we extract representative structures by decomposing the structure from a tree model expressing the XML document, and we perform clustering with the extracted structure. Besides, we show efficiency of proposed method by comparing and analyzing with the previous method.

• Journal of KIISE:Software and Applications
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• v.35 no.10
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• pp.608-615
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• 2008

In Knowledge Q&A services where information is created by unspecified users, document quality is an important factor of user satisfaction with search results. Previous work on quality prediction of Knowledge Q&A documents evaluate the quality of documents by using non-textual information, such as click counts and recommendation counts, and focus on enhancing retrieval performance by incorporating the quality measure into retrieval model. Although the non-textual information used in previous work was proven to be useful by experiments, data sparseness problem may occur when predicting the quality of newly created documents with such information. To solve data sparseness problem of non-textual features, this paper proposes new features for document quality prediction, namely text-confidence features, which indicate how trustworthy the content of a document is. The proposed features, extracted directly from the document content, are stable against data sparseness problem, compared to non-textual features that indirectly require participation of service users in order to be collected. Experiments conducted on real world Knowledge Q&A documents suggests that text-confidence features show performance comparable to the non-textual features. We believe the proposed features can be utilized as effective features for document quality prediction and improve the performance of Knowledge Q&A services in the future.

• Journal of the Korea Society of Computer and Information
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• v.29 no.9
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• pp.25-37
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• 2024

This study proposes a novel automation system that integrates Optical Character Recognition (OCR) and Retrieval-Augmented Generation (RAG) technologies to enhance the efficiency of the ESG (Environmental, Social, and Governance) document review process. The proposed system improves text recognition accuracy by applying an ensemble model-based image preprocessing algorithm and hybrid information extraction models in the OCR process. Additionally, the RAG pipeline optimizes information retrieval and answer generation reliability through the implementation of layout analysis algorithms, re-ranking algorithms, and ensemble retrievers. The system's performance was evaluated using certificate images from online portals and corporate internal regulations obtained from various sources, such as the company's websites. The results demonstrated an accuracy of 93.8% for certification reviews and 92.2% for company regulations reviews, indicating that the proposed system effectively supports human evaluators in the ESG assessment process.

• Journal of the Korea Computer Industry Society
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• v.5 no.1
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• pp.87-100
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• 2004

XML has recently considered as a new standard for data presentation and exchange on the web, many researches are on going to develop applications and index mechanism to store and retrieve XML documents efficiently. In this paper, design a Main-Memory based XML storage system for efficient management of XML document. And propose structured retrieval of XML document tree which reduce the traverse of XML document tree using element type information included user queries. Proposed indexing mechanism has flexibilities for dynamic data update. Finally, for query processing of XML document include Link information, design a index structure of table type link information on observing XLink standards.

• Journal of KIISE:Databases
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• v.37 no.2
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• pp.113-120
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• 2010

XML is broadly using for data storing and processing. XML is specified its structural characteristic and user can query with XPath when information from data document is needed. XPath query can process when the tern and structure of document and query is matched with each other. However, nowadays there are lots of data documents which are made by using different terminology and structure therefore user can not know the exact idea of target data. In fact, there are many possibilities that target data document has information which user is find or a similar ones. Accordingly user query should be processed when their term usage or structural characteristic is slightly different with data document. In order to do that we suggest a XML document ranking method based on path similarity. The method can measure a semantic similarity between user query and data document using three steps which are position, node and relaxation factors.

• The Journal of Information Technology
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• v.4 no.4
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• pp.89-100
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• 2001

XML (extensible Markup Language) is selected and published as a representative standard of electronic documents by W3C (World Wide Web Consortium). The structured information can be created and also transferred in XML documents. By utilizing XML, you can express the meaningful information unit as a structure comparing existed file typed information. With structured information, you can also manage retrieve, and reposit documents. According to the above facts, in this paper, it is the purpose to design and implement XML documents repository system to reposit and retrieve using structured information of XML documents. As a model it was designed to be stored by element unit which is the basic unit of documents and was also designed to retrieve the stored XML information by structured unit. It was, especially, designed to manage and reposit the structure of various documents effectively through creating schema as to DTD(Document Type Definition) and instance.

• Proceedings of the Korea Contents Association Conference
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• 2006.11a
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• pp.543-546
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• 2006

In this paper, we introduce a method to effectively highlight retrieval results without impairing meaningful features after historical documents were digitized into XML format. Especially, making the best of the features of historical documents, we perform string matching for the highlighting. Also, considering the features of the XML document, we carry out various processes when highlighting tag is inserted.

• Journal of Information Management
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• v.24 no.3
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• pp.1-30
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• 1993

Providing users who intend to retrieve document information in korean natural language with direct access to retrieval systems, a korean question processing system was developed in which korean natural language was translated into boolean search statements, which are the most frequently used in current information retrieval systems.

• Journal of the Korean Society for Library and Information Science
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• v.31 no.2
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• pp.199-215
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• 1997

The Internet has gained popularity because it provides various information in digital format. However, it is very difficult to provide methods which make it possible to search adequate information resource from bulk of Internet information. In this paper, we define a SGML metadata DTD, named SeriCore, and design and implement a metadata retrieval and management system which can store, retrieve and manage the Internet metadata efficiently.

• Journal of Korea Multimedia Society
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• v.13 no.5
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• pp.730-739
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• 2010

One of core technology in Web 2.0 is tagging, which is applied to multimedia data such as web document of blog, image and video etc widely. But unlike expectation that the tags will be reused in information retrieval and then maximize the retrieval efficiency, unacceptable retrieval results appear owing to toot limitation of tag. In this paper, in the base of preceding research about image retrieval through tag clustering, we design and implement a topic map generation system which is a semantic knowledge system. Finally, tag information in cluster were generated automatically with topics of topic map. The generated topics of topic map are endowed with mean relationship by use of WordNet. Also the topics are endowed with occurrence information suitable for topic pair, and then a topic map with semantic knowledge system can be generated. As the result, the topic map preposed in this paper can be used in not only user's information retrieval demand with semantic navigation but alse convenient and abundant information service.