• The Korean Journal of Archival Studies
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• no.78
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• pp.285-336
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• 2023

This study aims to analyze the system of official documents enacted during the modern reform period and the official documents produced in the provincial government office, scrutinizing the reality of management of the official documents that were conducted in the provincial government office at that time and organizing the characteristics. For this, I progressed this study targeting Changwon superintendent office that functioned as the modern government office among the provincial government office that existed during the modern reform period, and whose official documents produced in the government office remained relatively intact. At first, I summarized the history of Changwon area where Changwon superintendent office was installed. I investigated the geographical characteristics and the historical background in which Masanpo port of Changwon was opened in the past history and the superintendent office was installed. Following this, I categorized the function of Changwon superintendent office from the legal perspective, and reviewed the major contents of the official documents produced in the business activity and the historical context. Finally, I compared and analyzed the system of the official documents enacted at that time and their formats, organizing the official documents produced in the provincial government office during the modern reform period and the characteristics of the system of the official documents about the provincial government office.

• Journal of the Korea Society of Computer and Information
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• v.4 no.1
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• pp.21-27
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• 1999

In this paper. we propose a new method for automatic classification of documents using the degree of similarity between words. First, we seek relevance terms using automatic indexing. Second, we found frequency in use words in documents and the degree of relevance between the words using probability model. Continuously, we extracted the set of words which is connected the relevance closely and created the profiles characterizing each classification And, with the profile we finally classified them. We experimented on classifying two groups of documents. Some documents were about Genetic Algorithm. The others were about Neural Network. The results of the experiments indicated that automatic classification with word accordance of degree enable us to manage the retrieved documents structurally.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.6
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• pp.849-854
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• 2007

It is difficult that we collect only target documents from the Innumerable Web documents. One of solution to the problem is that we select target documents on the Web site which services many documents of target domain. In this paper, we will propose an intelligent crawling method collecting needed documents based on URL pattern script defined by XML. Proposed crawling method will efficiently apply to the sites which service structuralized information of a piece with database. In this paper, we collected 50 thousand Web documents using our crawling method.

• Journal of Korea Society of Industrial Information Systems
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• v.8 no.3
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• pp.61-68
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• 2003

In this paper, a representation method for structure information retrieval without schema and DTD of XML documents is presented. While existing researches have used DTD or schema to extract structure information, we extract structure information directly from XML documents. Especially the well-formed XML documents are only required to retrieve documents in the proposed method. Thus it can retrieve more general and various documents easily compared to the existing XML retrieval systems requiring DTD or schema. Experimental result indicates that the proposed method retrieves effectively structure information of XML documents independently to DTD information.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.11a
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• pp.53-56
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• 2003

Recent business environments require a company to communicate frequently with other companies. This makes it essential to use XML (extensible Markup Language) documents. Especially in e-Business environments, change management of documents is important to record and trace the history of the documents. It is also important to reconstruct a certain version of documents that are exchanged among companies. In this paper, we propose a new method of storing a document by detecting changes automatically and reconstructing the document version when a user requests. A prototype system is implemented on top of a workflow system. Our approach provides efficiency of storage space and convenient management of documents.

• The Journal of Information Systems
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• v.11 no.1
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• pp.175-198
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• 2002

This paper is to develop a security module for electronic approval systems. Electronic documents are created, transmitted and saved in the company's intranet computer network. Transmitting electronic documents, however, brings us a security problem. Communications among various computer systems are exposed to many security threats. Those threats are eavesdropping, repudiation, replay back etc. The main purpose of this paper is to develop a module which provides the security of electronic documents while they are passed from one place to another This paper applies Multi-Level security to the electronic approval system that guarantees security of electronic documents from many threats. Multi-Level security controls the access to the documents by granting security level to subject users and object electronic documents. To prevent possible replay back attacks, this paper also uses one time password to the system. The security module is composed of client program and server one. The module was developed using Microsoft Visual Basic 6.0 and Microsoft SQL Server 7.0. The code uses Richard Bondi's WCCO(Wiley CryptoAPI COM Objects) library functions which enables Visual Basic to access Microsoft CryptoAPI.

• The Journal of Information Technology and Database
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• v.8 no.1
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• pp.95-104
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• 2001

In the text classification domain, labeling the training documents is an expensive process because it requires human expertise and is a tedious, time-consuming task. Therefore, it is important to reduce the manual labeling of training documents while improving the text classifier. Selective sampling, a form of active learning, reduces the number of training documents that needs to be labeled by examining the unlabeled documents and selecting the most informative ones for manual labeling. We apply this methodology to Naive Bayes, a text classifier renowned as a successful method in text classification. One of the most important issues in selective sampling is to determine the criterion when selecting the training documents from the large pool of unlabeled documents. In this paper, we propose two measures that would determine this criterion : the Mean Absolute Deviation (MAD) and the entropy measure. The experimental results, using Renters 21578 corpus, show that this proposed learning method improves Naive Bayes text classifier more than the existing ones.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.13
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• pp.495-513
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• 2000

In this paper, I examined the terms of letter of credit and standard for examination of documents. In connection with the test of standard, I reviewed the bank's reasonable care, inconsistence and linkage between documents, non-documentary conditions and the treatment of discrepant documents. Traditionally credit law is founded on two principles such as the standards of strict of compliance and substantial compliance, but these standards are not consistency. Moreover although the Uniform Customs and Practice for Documentary Credits(UCP) introduces a new standard for examination of documents by incorporating international banking practice, the standards for documentary compliance have created ambiguity. Accordingly, I suggest that the standard requires strict compliance between party concerned in letter of credit transactions but only requires international standard banking practice in customer relationship. Therefore the standard and the specific guideline should be prescribed in the next version of the UCP.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.10a
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• pp.407-429
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• 2004

As documents in webs are increasing explosively due to the rapid development of electronic documents, an efficient system classifying documents automatically is required. In this study, a new document classification method, which is called Document Finger Print Method, is suggested to classify web documents automatically and efficiently. The performance of the suggested method is evaluated alone with other existing methods such as key words based method, weighted key words based method, neural networks, and decision trees. An experiment is designed with 10 documents categories and 59 randomly selected words. The result shows that the suggested algorithm has a superior classifying performance compared to other methods. The most important advantage of this method is that the suggested method works well without the size limits of the number of words in documents.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.3
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• pp.153-158
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• 2015

Nowadays, automatic keyphrase extraction is considered to be an important task. Most of the previous studies focused only on selecting keyphrases within the body of input documents. These studies overlooked latent keyphrases that did not appear in documents. In addition, a small number of studies on latent keyphrase extraction methods had some structural limitations. Although latent keyphrases do not appear in documents, they can still undertake an important role in text mining because they link meaningful concepts or contents of documents and can be utilized in short articles such as social network service, which rarely have explicit keyphrases. In this paper, we propose a new approach that selects qualified latent keyphrases from input documents and overcomes some structural limitations by using deep belief networks in a supervised manner. The main idea of this approach is to capture the intrinsic representations of documents and extract eligible latent keyphrases by using them. Our experimental results showed that latent keyphrases were successfully extracted using our proposed method.