• KNOM Review
• /
• v.24 no.1
• /
• pp.29-37
• /
• 2021

With the spread of the Internet, users can easily receive various services and exchange information through the web. There are several requirements for building a web system, and it must be developed using a programming language or platform for user purposes. Residual material information refers to information on medicines and pesticides added to food, and residual material standards are used to measure the level of residues in food produced by companies and farmers to determine whether those levels meet domestic or international standards. Currently, the Ministry of Food and Drug Safety provides residual acceptance standards for food additives, including food, pesticides and animal medicines, in the form of documents, which must be serviced smoothly and conveniently by users through the establishment of a web system. It must also meet a variety of requirements, including user accessibility, such as scalability and compatibility. This paper proposes react-based residual material information web system that allows users to access more conveniently and receive residual material information smoothly. We measured the speed for the three inportant functions of information provision and compared them with existing residual material information web systems and qualitatively evaluated the seven essential requirements: scalability, compatibility, and accessibility.

• The Journal of Society for e-Business Studies
• /
• v.13 no.2
• /
• pp.213-223
• /
• 2008

The efficient discovery of services from a large scale collection of services has become an important issue[7, 24]. We studied a syntactic method for Web service discovery, rather than a semantic method. We regarded a service discovery as a retrieval problem on the proprietary XML formats, which were service descriptions in a registry DB. We modeled services and queries as probabilistic values and devised similarity-based retrieval techniques. The benefits of our way are follows. First, our system supports ranked service retrieval by keyword search. Second, we considers both of UDDI data and WSDL definitions of services amid query evaluation time. Last, our technique can be easily implemented on the off-theshelf DBMS and also utilize good features of DBMS maintenance.

• Journal of Korean Society of Archives and Records Management
• /
• v.12 no.1
• /
• pp.141-165
• /
• 2012

Since 'the National Assembly Electronic Document System' was introduced in September 2004, the amount of electronic records production in the Nation Assembly has been on a rapid increase. The number of electronic records which 'the National Assembly Records Management System' took over until September 2011 is '240,000', 72% of the total transferred records. However, the National Assembly's electronic records management has a number of serious problems concerning electronic records long-term management and preservation. In the context, this study aims at discussing alternative strategies for effective management and preservation of the Nation Assembly electronic records. In the theoretical aspect, it reviews 'parliament records' definition and management trend. As a case study, it explores the present state of 'the National Assembly Records Management System' ranging from legal aspects to technical aspects. Based on these researches the study critically analyzes the Nation Assembly's electronic records management in comparison with overseas cases. As a result it provides alternative plans of four major areas, including law, management body, management object and technical system, to improve the National Assembly's electronic records management.

• Journal of the Korean Society for information Management
• /
• v.24 no.2
• /
• pp.123-141
• /
• 2007

It has been known that predicting stock price is very difficult due to a large number of known and unknown factors and their interactions, which could influence the stock price. However, we started with a simple assumption that good news about a particular company will likely to influence its stock price to go up and vice versa. This assumption was verified to be correct by manually analyzing how the stock prices change after the relevant news stories were released. This means that we will be able to predict the stock price change to a certain degree if there is a reliable method to classify news stories as either favorable or unfavorable toward the company mentioned in the news. To classify a large number of news stories consistently and rapidly, we developed and evaluated a natural language processing based multi-stage news classification system, which categorizes news stories into either good or bad. The evaluation result was promising as the automatic classification led to better than chance prediction of the stock price change.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.24 no.5
• /
• pp.470-476
• /
• 2014

A point of interest is a specific point location such as a cafe, a gallery, a shop, or a park. It consists of a name, a category, a location, and so on. Its information is necessary for location-based application, above all category is basic information. However, category information should be automatically gathered because it costs high to gather it manually. In this paper, we propose a novel method to estimate category of POIs automatically using an inner word and local context. An inner word is a word that contains POI's name. Their name sometimes expose category information. Thus, their name is used as inner word information in estimating category of POIs. Local context information means words around a POI's name in a document that mentioned the name. The context include information to estimate category. The evaluation of the proposed method is performed on two data sets. According to the experimental results, proposed model using combination inner word and local context show higher accuracy than that of model using each.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.24 no.6
• /
• pp.640-645
• /
• 2014

Many people use social network services as to communicate, to share an information and to build social relationships between others on the Internet. Twitter is such a representative service, where millions of tweets are posted a day and a huge amount of data collection has been being accumulated. Social mining that extracts the meaningful information from the massive data has been intensively studied. Typically, Twitter easily can deliver and retweet the contents using the following-follower relationships. Topic modeling in tweet data is a good tool for issue tracking in social media. To overcome the restrictions of short contents in tweets, we introduce a notion of reply graph which is constructed as a graph structure of which nodes correspond to users and of which edges correspond to existence of reply and retweet messages between the users. The LDA topic model, which is a typical method of topic modeling, is ineffective for short textual data. This paper introduces a topic modeling method that uses reply graph to reduce the number of short documents and to improve the quality of mining results. The proposed model uses the LDA model as the topic modeling framework for tweet issue tracking. Some experimental results of the proposed method are presented for a collection of Twitter data of 7 days.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.24 no.4
• /
• pp.184-193
• /
• 2021

The system for managing spatial data updates the existing information by extracting only the information that is different from the existing information for the newly obtained spatial information file to update the stored information. In order to extract only objects that have changed from existing information, it is necessary to compare whether there is any difference from existing information for all objects included in the newly obtained spatial information file. This study was conducted to improve this total inspection method in a situation where the amount of spatial information that is frequently updated increases and data update is required at the national level. In this study, before inspecting individual objects in a new acquisition space information file, a method of determining whether individual space objects have been changed only by the information in the file was considered. Spatial data files have structured data characteristics different from general image or text document files, so it is possible to determine whether to change the file unit in a simpler way compared to the existing method of creating and managing file hash. By reducing the number of target files that require full inspection, it is expected to improve the use of resources in the system by saving the overall data quality inspection time and saving data extraction time.

• Journal of the Korean Society for information Management
• /
• v.28 no.1
• /
• pp.145-170
• /
• 2011

The purpose of this paper is to suggest a pilot model of knowledge organizing system which reflects the knowledge structure of research papers, using a case analysis on the "Korean Research Memory" of the National Research Foundation of Korea. In this paper, knowledge structure of the research papers in humanities and social science is described and the function of the "Korean Research Memory" for scholarly sense-making is analysed. In order to suggest the pilot model of the knowledge organizing system, the study also analysed the relation between indexed keyword and knowledge structure of research papers in the Korean Research Memory. As a result, this paper suggests 24 axioms and 11 inference rules for an ontology based on semantic relation of the knowledge structure.

• Information Systems Review
• /
• v.8 no.1
• /
• pp.1-24
• /
• 2006

Now, the Korean footwear industry needs the concrete enhancement of its competitive edge for regaining of its previous well known reputation. For this purpose, this study emphasizes the cooperation between the members through the supply chain of Korean footwear industry, as a c-SCM(Collaborative Supply Chain Management) by aid of information system. The key issue will be how well to coordinate operations flow not only through internal process stages, but also through entire external supply chain stages. In other words, the target goal must be the system optimization through the entire supply chain beyond the local optimization of internal supply chain process. We, at first, analyze the traditional structure of supply chain in Korean footwear industry and find out critical problems, and then, we develop the collaborative information framework in conjunction with several collaborative process modules. The suggested collaborative production & supply planning system was designed for sharing information and it is based on ebXML(electronic business eXtensible Markup Language) framework. In this way, the enhancement of the efficiency and competitiveness can be expected through the synergy effect of coordination of information and material flow, the reduction of lead times, and production costs.

• Journal of Intelligence and Information Systems
• /
• v.24 no.1
• /
• pp.141-166
• /
• 2018

Information technology improves the efficiency of humanities research. In humanities research, information technology can be used to analyze a given topic or document automatically, facilitate connections to other ideas, and increase our understanding of intellectual history. We suggest a method to identify and automatically analyze the relationships between arguments contained in unstructured data collected from humanities writings such as books, papers, and articles. Our method, which is called history mining, reveals influential relationships between arguments and the philosophers who present them. We utilize several classification algorithms, including a deep learning method. To verify the performance of the methodology proposed in this paper, empiricists and rationalism - related philosophers were collected from among the philosophical specimens and collected related writings or articles accessible on the internet. The performance of the classification algorithm was measured by Recall, Precision, F-Score and Elapsed Time. DNN, Random Forest, and Ensemble showed better performance than other algorithms. Using the selected classification algorithm, we classified rationalism or empiricism into the writings of specific philosophers, and generated the history map considering the philosopher's year of activity.