• The KIPS Transactions:PartB
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• v.12B no.7 s.103
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• pp.811-822
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• 2005

Automated text categorization is to classify free text documents into predefined categories automatically and whose main goals is to reduce considerable manual process required to the task. The researches to improving the text categorization performance(efficiency) in recent years, focused on enhancing existing classification models and algorithms itself, but, whose range had been limited by feature based statistical methodology. In this paper, we propose RTPost system of different style from i.ny traditional method, which takes fault tolerant system approach and data mining strategy. The 2 important parts of RTPost system are reinforcement training and post-processing part. First, the main point of training method deals with the problem of defining category to be classified before selecting training sample documents. And post-processing method deals with the problem of assigning category, not performance of classification algorithms. In experiments, we applied our system to documents getting low classification accuracy which were laid on a decision boundary nearby. Through the experiments, we shows that our system has high accuracy and stability in actual conditions. It wholly did not depend on some variables which are important influence to classification power such as number of training documents, selection problem and performance of classification algorithms. In addition, we can expect self learning effect which decrease the training cost and increase the training power with employing active learning advantage.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2003.05a
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• pp.246-254
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• 2003

행위범주를 이용한 구조에서 가장 중요한 특징 두가지는 첫째 행위의 계층을 주종이며 정적인 계층으로 구분하지 않고 행위 범주별 구분을 하여 복잡한 환경에 유연하게 대처할 수 있다. 둘째, 모든 행위를 객체화 하여 처리한다. 객체화 된 행위는 스스로의 문제점을 감시하고 처리하거나 보고하여 전체 구조의 간편화를 가져오게 된다. 본 논문에서는 행위를 범주 구분을 위하여 필요한 행위 설계 방식을 제시하고 행위 객체를 위한 구성요소를 소개한다.

• Journal of KIISE:Software and Applications
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• v.29 no.6
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• pp.417-424
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• 2002

Automatic text categorization is a problem of assigning predefined categories to free text documents. In order to classify text documents, we have to extract good features from them. In previous researches, a text document is commonly represented by the frequency of each feature. But there is a difference between important and unimportant sentences in a text document. It has an effect on the importance of features in a text document. In this paper, we measure the importance of sentences in a text document using text summarizing techniques. A text document is represented by features with different weights according to the importance of each sentence. To verify the new method, we constructed Korean news group data set and experiment our method using it. We found that our new method gale a significant improvement over a basis system for our data sets.

• KIISE Transactions on Computing Practices
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• v.22 no.6
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• pp.290-295
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• 2016

Recently, folksonomy-based image-sharing sites where users cooperatively make and utilize tags of image annotation have been gaining popularity. Typically, these sites retrieve images for a user request using simple text-based matching and display retrieved images in the form of photo stream. However, these tags are personal and subjective and images are not categorized, which results in poor retrieval accuracy and low user satisfaction. In this paper, we propose a categorization scheme for folksonomy images which can improve the retrieval accuracy in the tag-based image retrieval systems. Consequently, images are classified by the semantic similarity using text-information and image-information generated on the folksonomy. To evaluate the performance of our proposed scheme, we collect folksonomy images and categorize them using text features and image features. And then, we compare its retrieval accuracy with that of existing systems.

• Journal of KIISE:Software and Applications
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• v.27 no.4
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• pp.384-392
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• 2000

As a software becomes more complicated and large-scaled, it is very important for a software engineer to analyze user's requirements precisely and apply them effectively in the development stage. Due to the growth of the internet, the necessity of requirements elicitation and analysis in distributed environments has also become larger. This paper proposes a requirements elicitation supporting system that offer the basis for effectively analyzing requirements collected in distributed environments. The proposed system automatically categorizes collected requirements sentences into selected subject fields by measuring their similarity using a similarity measurement technique. Therefore, it reduces the difficulties in the initial stage of requirements analysis and it supports rapid and correct requirements analysis. This paper verifies the efficiency of the proposed system in similarity measurement techniques through experiments, and presents a process for requirements specifications elicitation using the embodied system

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.39 no.3
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• pp.71-82
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• 2002

The software pattern is knowledge representation derived from the verified solutions or the experience of the experts. On account of the design varieties of software development, however, it is not the facilitated task to discover the best proper software pattern. This situation requires that software patterns be categorized in terms of their innate concepts. This paper proposes software pattern ontology(SPO) for the systematic categorization of software patterns by means of conceptual properties of patterns after the comparative analysis of association between software pattern and ontology. The SPO presented in this paper can establish the basis for the software pattern management system at the conceptual level. This paper also shows an idea for the application by unifying conceptual properties of software pattern and ontology. 

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.5
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• pp.1097-1114
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• 2015

As the online game market grows, illegal activities such as cheating play using game bots or game hack programs, running private servers, hacking game companies' system and network, and account theft are also increasing. There are various security measures for online games to prevent illegal activities. However, the current security measures are not enough to prevent all highly evolving game attacks and frauds. Some security measure can do harm game players usability, game companies need to develop usable security measure that is well fit to game genre and contents design. In this study, we surveyed the recent trend of various security measure applied in online games. This research also classified illegal activities and their related countermeasure for detection and prevention.

• Information Systems Review
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• v.5 no.2
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• pp.151-168
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• 2003

A knowledge portal is an integrated gateway for accessing relevant knowledge, collaborating and communicating with other users, and also linking internal applications which is becoming crucial in the age of information abundance. Research and development is a typical knowledge-intensive activity. However, knowledge management support in R&D has been minimal in most research organizations. In this paper, a knowledge portal is designed to support team-based researches in science and technology for searching and browsing knowledge, and also communicating with other team members, coordinating research project and collaborating with other researchers. Automating knowledge acquisition from various knowledge sources, knowledge categorization by applying text categorization method, and knowledge recommendation can help to relieve management effort and increase the efficiency of knowledge management processes. A prototype system based on the suggested model is also presented.

• International Journal of Advanced Culture Technology
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• v.7 no.2
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• pp.125-136
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• 2019

This study focuses(selected) on garden facilities of designer gardens created at the 1st and 2nd Seoul Garden Shows and examined installed facilities at each designer garden by categorization according to type, material and functions. The study observed problems occurring from maintenance of garden facilities as time passes by and collected basic data to develop maintenance guideline aiming to make contribution to further spreading and promotion of high quality garden culture. This study examined all gardens created at 1st and 2nd Seoul Garden shows in 2015 and 2016. There were 18 gardens built in 2015 and 16 in 2015.The study looked at responsible entities for maintenance of facilities and examined maintenance system for managing these gardens. Garden facilities of the study were categorized into paving, facility for rest, playground, water facility, environmental sculpture and planting media facility according to categorization by landscape design standards and construction guidelines. Target gardens of this study are maintained mostly by citizen gardeners who are passionately carrying out maintenance work while communicating with designers. However, these citizen gardeners lack technical knowledge to manage various facilities. Also, maintenance manuals submitted by garden designers do not offer sufficient details on facility maintenance which calls for professional maintenance and clear instructions on facilities from early phase of design.

• Korean Journal of Cognitive Science
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• v.13 no.3
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• pp.33-46
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• 2002

Recently, unstructured random data such as website logs, texts and tables etc, have been flooding in the internet. Among these unstructured data there are potentially very useful data such as bulletin boards and e-mails that are used for customer services and the output from search engines. Various text mining tools have been introduced to deal with those data. But most of them lack accuracy compared to traditional data mining tools that deal with structured data. Hence, it has been sought to find a way to apply data mining techniques to these text data. In this paper, we propose a text mining system which can incooperate existing data mining methods. We use text mining as a preprocessing tool to generate formatted data to be used as input to the data mining system. The output of the data mining system is used as feedback data to the text mining to guide further categorization. This feedback cycle can enhance the performance of the text mining in terms of accuracy. We apply this method to categorize web sites containing adult contents as well as illegal contents. The result shows improvements in categorization performance for previously ambiguous data.