• 지능정보연구
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• 제1권1호
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• pp.23-41
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• 1995

Business researchers have traditionally used statistical techniques for classification. In late 1980's, inductive learning started to be used for business classification. Recently, neural network began to be a, pp.ied for business classification. This study reviews the business classification studies, identifies a neural network a, pp.oach as the most powerful classification tool, and discusses the problems and issues in neural network a, pp.ications.

• International Journal of Railway
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• 제2권1호
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• pp.37-42
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• 2009

Information management of products and services in every industries is gaining importance for resource planning and maintenance. In this paper, we analyzed the information classification systems for railway industry. International and domestic classification systems, such as HS, UNSPSC, eCl@ss and ISIC, are reviewed; as a result this paper presents the findings and the various issues. We proposed to-be images in adopting and utilizing the classification systems. Using the integrative information classification systems could make efficient electronic procurement, supply chain management and e-Business of railway services.

• 통상정보연구
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• 제6권3호
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• pp.41-61
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• 2004

Today, most companies are needed to become interested on e-Biz and information management system. Especially, Data classification format system was very important for application to effective and efficiency management decision support. They should include main entry which consists of department, employee's name, title, publication date. Now, each company is using eleven different methods on data classification format system. In this paper finding result was as follows, in other words, general management document case using the nine date classification methods and special report management document ca se using the twodata classification methods. The aim of this study is to investigate problems that the present data classification format system has and some concerns that should be taken into account in case of the modification of the data classification system and change into a new one. This study is based on the survey in that the company managergave to 35 companies throughout the nation. As a result, the survey indicates that the crucial concerns of the participating managers are ineffective management information source and the duplication of data classification systems. This paper is the transcendental study the introduction of data classification format systems to business companies in Korea. This paper provided the fundamental data for the effective business process reengineering in business activity for management information.

• Asia pacific journal of information systems
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• 제17권1호
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• pp.33-58
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• 2007

Quiet often, an organization tries to grapple with inconsistent and partial information to generate relevant information to support decision making and action. As such, an organization scans the environment interprets scanned data, executes actions, and learns from feedback of actions, which boils down to computational interpretations and learning in terms of machine learning, statistics, and database. The ExOM proposed in this paper is geared to facilitate such knowledge discovery found in large databases in a most flexible manner. It supports a broad range of learning and classification styles and integrates them with traditional database functions. The learning and classification components of the ExOM are tightly integrated so that learning and classification of objects is less burdensome to ordinary users. A brief sketch of a strategy as to the expressiveness of terminological language is followed by a description of prototype implementation of the learning and classification components of the ExOM.

• Journal of Information Technology Applications and Management
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• 제9권3호
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• pp.129-139
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• 2002

There exist a number of information systems planning (ISP) methodologies. Historically these methodologies have been evolving to reflect new technologies and business requirements. In fact, it is an uneasy task to select a methodology that fits a business need. Though there have been a number of studies proposing new ISP approaches, we are unable to find much research doing a comparative analysis on existing ISP methodologies. Our study, therefore, is to present a classification scheme for ISP approaches and to provide a guideline framework for selecting an approach most suitable to a particular firm's need. Our classification utilizes types of components covered in ISP deliverables and the peculiarity of these components. Such classification scheme and selection framework would help derive an IT-driven new enterprise model more effectively.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2004년도 춘계학술대회
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• pp.2059-2063
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• 2004

Most power plants have operated many independent computerize systems for maintenance. Independence of systems have caused complexity of business process and inconvenience of computer system management. Because the equipment and material master data is not standardize and structurize, it is difficult to manage equipment maintenance history and material delivery. Especially equipment classification criterion is important for standardization of every maintenance information. It is necessary to integrate function of independent systems for business process simplification and rapid work flow. this paper provides equipment classification criterion design and system integration method with the case of live system development.

• 경영정보학연구
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• 제3권2호
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• pp.245-260
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• 2001

While past knowledge management researches have focused on conceptualization and strategic implications, knowledge asset researches attempt to provide practical guidelines for companies. However, each research classifies knowledge asset from its own perspective, and thus it is not a trivial task to leverage consistent and inclusive criteria in managing corporate knowledge asset. The objective of this paper is to develop a knowledge asset classification schema on the basis of the three business functions: customer relationship management, product innovation, and infrastructure management. To demonstrate the feasibility of our schema, it has been applied to 9 Korean corporations. Knowledge assets are evaluated according to core capabilities, which are main drivers of sustainable competitive advantages. The results of case study show that the leveraged classification schema reflects current knowledge asset management and characteristics of corporations. Our finding is that most top-quality knowledge management corporations are likely to develop well-balanced knowledge asset.

• 한국신뢰성학회지:신뢰성응용연구
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• 제10권3호
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• pp.183-197
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• 2010

Web businesses are one of the most dynamic industries where lots of new business models are emerging while the other obsoleted ones are fading away almost every day. It is, therefore, difficult to establish a classification scheme for ever-changing web businesses. Previous researches on business models focus on classifying web businesses in one dimension which made some web sites difficult to fit into one category. We propose two dimensional classification scheme based on the means and the sources of revenue. The two dimensional classification provides more clear and broad perspectives of the web businesses and ways to identify web sites in combinations of several business models.

• Asia pacific journal of information systems
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• 제29권4호
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• pp.771-788
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• 2019

Deep learning techniques such as Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) show superior performance in text classification than traditional approaches such as Support Vector Machines (SVMs) and Naïve Bayesian approaches. When using CNNs for text classification tasks, word embedding or character embedding is a step to transform words or characters to fixed size vectors before feeding them into convolutional layers. In this paper, we propose a parallel word-level and character-level embedding approach in CNNs for text classification. The proposed approach can capture word-level and character-level patterns concurrently in CNNs. To show the usefulness of proposed approach, we perform experiments with two English and three Korean text datasets. The experimental results show that character-level embedding works better in Korean and word-level embedding performs well in English. Also the experimental results reveal that the proposed approach provides better performance than traditional CNNs with word-level embedding or character-level embedding in both Korean and English documents. From more detail investigation, we find that the proposed approach tends to perform better when there is relatively small amount of data comparing to the traditional embedding approaches.

• 경영정보학연구
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• 제10권3호
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• pp.89-109
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• 2008

후발카드사들의 시장 확대 전략, 은행계 카드사의 약진 등 점차 치열해지는 경쟁 구도에 대비하기 위해 S카드사는 과거와 같이 단순 신용카드 상품이나 '고수익 고위험'의 대출서비스에 주력하는 수익모델로는 향후 생존하기 어렵다는 현실을 인식하고 신용판매 활동의 내실 강화를 통해 지속적으로 수익을 창출할 수 있는 방안을 강구하였는데 이것이 바로 가맹점 업종분류체계 정비를 통한 고객세분화이다. 즉, 기존의 수수료율 책정기준으로 만들어진 가맹점 업종분류체계를 마케팅 목적으로 재편하고 새로운 업종분류체계에 맞춰 고객의 정확한 카드 사용실적을 파악한 후 고객을 세분화하는 개념으로, 가맹점과 고객의 다양한 니즈를 연계 관리함으로써 고객에게는 맞춤 정보 및 오퍼를 제공하고, 가맹점과의 긴밀한 협력관계를 통해 가맹점 매출을 증대하며, 이로 인해 자사의 신용판매를 확대하고 수익을 극대화하는 고객, 가맹점, 자사 상호간의 Win-Win-Win 관계 형성을 목표로 하였다. 본 연구에서는 S카드사가 어떠한 방식으로 기존의 업종분류체계를 정비하여 고객세분화를 수행하였으며, 어떻게 활용하고 있는가를 살펴봄으로써 효과적인 고객세분화에 기반한 마케팅 전략수립 의 방향을 제시하고자 한다.