• Proceedings of the Korea Database Society Conference
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• 1999.06a
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• pp.105-113
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• 1999

최근 데이터와 데이터베이스의 폭발적 증가에 따라 무한한 데이터 속에서 정보나 지식을 찾고자하는 지식채굴과정 (knowledge discovery process)에 대한 관심이 높아지고 있다. 특히 기업 내외부 데이터베이스 뿐만 아니라 데이터웨어하우스 (data warehouse)를 기반으로 하는 OLAP환경에서의 데이터와 인터넷을 통한 웹 (web)에서의 정보 등 정보원의 다양화와 첨단화에 따라 다양한 환경 하에서의 지식채굴과정이 요구되고 있다. 본 연구에서는 인터넷 상의 지식을 효과적으로 채굴하기 위한 지식채굴과정을 제안한다. 제안된 지식채굴과정은 명시지 (explicit knowledge)외에 암묵지 (tacit knowledge)를 지식채굴과정에 반영하기 위해 선행지식베이스 (prior knowledge base)와 선행지식관리시스템 (prior knowledge management system)을 이용한다. 선행지식관리시스템은 퍼지인식도(fuzzy cognitive map)를 이용하여 선행지식베이스를 구축하여 이를 통해 웹에서 찾고자 하는 유용한 정보를 정의하고 추출된 정보를 지식변환시스템 (knowledge transformation system)을 통해 통합적인 추론과정에 사용할 수 있는 형태로 변환한다. 제안된 연구모형의 유용성을 검증하기 위하여 재무자료에 선행지식을 제외한 자료와 선행지식을 포함한 자료를 사례기반추론 (case-based reasoning)을 이용하여 실험한 결과, 제안된 지식채굴과정이 유용한 것으로 나타났다.

• Journal of Korean Library and Information Science Society
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• v.42 no.1
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• pp.397-415
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• 2011

Google, an internet search service with extensive user base, has provided Book Search service. Google has pursued collaboration with publishers and libraries to obtain content for Book Search service; publisher community for the purpose of sourcing the books with copyrights, and the libraries for the purpose of digitizing their collections and also utilizing already digitized resources. Google Book Search Service has evoked significant controversy because of the potential monopoly problems and its risk, accompanied by Google's huge influence and broad user spectrum. This study, thus, suggests the countermeasures that library community should prepare in order to cope with the Google Book Search.

• Korean Journal of Ecology and Environment
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• v.39 no.1 s.115
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• pp.131-137
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• 2006

Most South Korean lakes are middle/small size artificial reservoirs, which are almost agricultural reservoirs (17,956). A total of 67 species (21 families) were recorded and collected from 65 agricultural reservoirs though field samplings and literature surveys. Dominant species was Pseudorasbora parva (relative abundance 24.5%), and Carassius auratur (41 sites) was the highest frequency. Feeding group of fish communities in the reservoirs was as follows: carnivorous (16.2%), omnivorous (79.5%) and herbivorous fish (4.3%). The number of individuals (P=0.024), species number (P=0.047) and carnivores number (P=0.024) were significantly correlated with reservoir ages. Reservoirs were classified into 3 groups according to feeding patterns of carnivore, omnivore and herbivore groups. The omnivores were dominant group in agricultural reservoirs. Detailed studies on fish community will be a base for the understanding of food web structure and biomanipulation in reservoir systems.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.03a
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• pp.105-113
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• 1999

최근 데이터와 데이터베이스의 폭발적 증가에 따라 무한한 데이터 속에서 정보나 지식을 찾고자하는 지식채굴과정(Knowledge discovery process)에 대한 관심이 높아지고 있다. 특히 기업 내외부 데이터베이스 뿐만 아니라 데이터웨어하우스(data warehouse)를 기반으로 하는 OLAP 환경에서의 데이터와 인터넷을 통한 웹(web)에서의 정보 등 정보원의 다양화와 첨단화에 따라 다양한 환경 하에서의 지식 채굴과정이 요구되고 있다. 본 연구에서는 인터넷 상의 지식을 효과적으로 채굴하기 위한 지식채굴과정을 제안한다. 제안된 지식채굴과정은 명시지(explicit knowledge)외에 암묵지(tacit knowledge)를 지식채굴과정에 반영하기 위해 선행지식베이스(prior knowledge base)와 선행지식관리시스템(prior knowledge management system)을 이용한다. 선행지식관리시스템은 퍼지인식도(fuzzy cognitive map)를 이용하여 선행지식베이스를 구축하여 이를 통해 웹에서 찾고자 하는 유용한 정보를 정의하고 추출된 정보를 지식변환시스템(knowledge transformation system)을 통해 통합적인 추론과정에 사용할 수 있는 형태로 변환한다. 제안된 연구모형의 유용성을 검증하기 위하여 재무자료에 선행지식을 제외한 자료와 선행지식을 포함한 자료를 사례기반추론 (case-based reasoning)을 이용하여 실험한 결과, 제안된 지식채굴과정이 유용한 것으로 나타났다.

• Korean Management Science Review
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• v.17 no.3
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• pp.19-30
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• 2000

Customization and personalization services are considered as a critical success factor to be a successful Internet store or web service provider. As a representative personalization technique, personalized recommendation techniques are studied and commercialized to suggest products or services to a customer of Internet storefronts based on demographics of the customer or based on an analysis of the past purchasing behavior of the customer. The underlining theories of recommendation techniques are statistics, data mining, artificial intelligence, and/or rule-based matching. In the rule-based approach for personalized recommendation, marketing rules for personalization are usually collected from marketing experts and are used to inference with customers data. however, it is difficult to extract marketing rules from marketing experts, and also difficult to validate and to maintain the constructed knowledge base. In this paper, we proposed a marketing rule extraction technique for personalized recommendation on Internet storefronts using market basket analysis technique, a well-known data mining technique. Using marketing basket analysis technique, marketing rules for cross sales are extracted, and are used to provide personalized advertisement selection when a customer visits in an Internet store. An experiment has been performed to evaluate the effectiveness of proposed approach comparing with preference scoring approach and random selection.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2001.10a
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• pp.7-10
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• 2001

The development of information communication technology leads the growth of logistic industry including delivery service as well as electronic commerce. The researchers predict that it will be still improving for the next several years. The logistic information system of railroad courier has been growing for a long time with small-package delivery transportation which is similar to the land-road delivery system. Despite of the long-time growth, it is recently in pain of the great loss since the 1990's, due to the failure to satisfy the customer's need for door-to-door delivery service. But the logistic information system of railroad still has the great potential. There are so many benefits such as timeliness, Punctuality, speed, multi-node storage base, transportation efficiency, energy frugality, environmental sociability, and so on. If the railroad logistic system plays a role of a portion of the nation-wide logistic with other logistic system, the synergy through the balancing logistic will also get much of international competitive advantages. So the objective of this research is to design the model and prototype of the web-based logistic system from which railroad service provider(Korean National Railroad), delivery service providers, and the customers can share the best effective delivery information.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.9
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• pp.1549-1559
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• 2010

Modern power system is operated and managed in closed network environment with treating a great variety of data, and requirement of real time power system data is more increasing. However, it is difficult for operators to fast evaluate the condition of power system using only isolation network system such as SCADA or EMS regarding unexpecting situations occurring. Recent technology achievement in areas of distributed computing, networking high speed communications and digital control as well as the availability of accurate GPS time source are rapidly becoming the enabling factors for the development of a new generation of real time power grid monitoring tools. In this paper, architecture of WAMAC which is the wide area monitoring and control system not only to control but also to monitoring in real time is proposed and the plan of integration interface with legacy system such as EMS for providing power system analysis base data effectively is suggested.

• IE interfaces
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• v.24 no.3
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• pp.248-257
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• 2011

The amount of Meta-data to be managed increases with development of information technology. However, when trying to integrate and share product information of heterogeneous systems within or between companies, sharing of information is impossible if product information classification systems are different. Due to the situation mentioned above, engineers judge the product information classification system and maps corresponding Meta-data for document-based sharing. Judging exponentially increasing amount of data by engineers and sharing product information using documents create great amount of time delay and errors in data handling. Therefore, construction of a system for integrated management and interoperability between product information based on semantic information similar to engineer's judgment is required. This paper proposes a methodology and necessity of a system for interoperability of product information based on semantic web, and also designs a system to integrate heterogeneous systems with different product information using rule based reasoning. This paper also suggests a system base for interoperability and integration of product information between heterogeneous systems by integrating the product information classification system semantically.

• Journal of Korean Institute of Industrial Engineers
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• v.43 no.3
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• pp.192-202
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• 2017

This study develops a text spam filtering system for Facebook based on two variable categories: keywords learned from Instagram and meta-information of Facebook posts. Since there is no explicit labels for spam/ham posts, we utilize hash tags in Instagram to train classification models. In addition, the filtering accuracy is enhanced by considering meta-information of Facebook posts. To verify the proposed filtering system, we conduct an empirical experiment based on a total of 1,795,067 and 761,861 Facebook and Instagram documents, respectively. Employing random forest as a base classification algorithm, experimental result shows that the proposed filtering system yield 99% and 98% in terms of filtering accuracy and F1-measure, respectively. We expect that the proposed filtering scheme can be applied other web services suffering from massive spam posts but no explicit spam labels are available.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.2
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• pp.125-133
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• 2009

RDF is widely used as the ontology language for representing metadata on the semantic web. Since ontology models the real-world, ontology changes overtime. Thus, it is very important to detect and analyze changes in knowledge base system. Earlier studies on detecting changes between RDF models focused on the structural differences. Some techniques which reduce the size of the delta by considering the RDFS entailment rules have been introduced. However, inferencing with RDF models increases data size and upload time. In this paper, we propose a new change detection using RDF reasoning that only computes a small part of the implied triples using backward chaining strategy. We show that our approach efficiently detects changes through experiments with real-life RDF datasets.