• Journal of Intelligence and Information Systems
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• v.8 no.1
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• pp.119-139
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• 2002

In electronic catalogs, each item is represented as an independent unit while the parts of the item can be composed of a higher level of functionality. Thus, the search for this kind of product database is limited to the retrieval of most similar standard commodities. However, many industrial products need to configure optional parts to fulfill the required specifications. Since there are many paths in finding the required specifications, we need to develop a search system via the configuration process. In this system, we adopt a two-phased approach. The first phase finds the most similar template, and the second phase adjusts the template specifications toward the required set of specifications by the Constraint and Rule Satisfaction Problem approach. There is no guarantee that the most similar template can find the most desirable configuration. The search system needs backtracking capability, so the search can stop at a satisfied local optimal satisfaction. This framework is applied to the configuration of computers and peripherals. Template-based reasoning is basically the same as case-based reasoning. The required set of specifications is represented by a list of criteria, and matched with the product specifications to find the closest ones. To measure the distance, we develop a thesaurus of values, which can identify the meaning of numbers, symbols, and words. With this configuration, the performance of the search by configuration algorithm is evaluated in terms of feasibility and admissibility.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.3
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• pp.59-68
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• 2012

Zero client-based cloud storage technology is gaining much interest as a tool to centralized management of organizational documents nowadays. Besides the well-known cloud storage's defects such as security and privacy protection, users of the zero client-based cloud storage point out the difficulty in browsing and selecting the storage category because of its diversity and complexity. To resolve this problem, this study proposes a method of intelligent document archiving by applying an algorithm-based automatic topic identification technology. Without user's direct definition of category to store the working document, the proposed methodology and prototype enable the working documents to be automatically archived into the predefined categories according to the extracted topic. Based on the proposed ideas, more effective and efficient centralized management of electronic documents can be achieved.

• Journal of Convergence for Information Technology
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• v.12 no.1
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• pp.15-21
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• 2022

In the content-based video retrieval applications, the information on the movement of an object can be used as important in classifying the content. In particular, analyzing and classifying human movement can be used for various purposes as well as retrieval. In this paper, a method to improve the performance of the shape variation descriptor and shape sequence to describe and classify movement using shape information that changes according to the movement of an object is proposed. By selecting a shape descriptor to more efficiently describe the shape information of an object and comparing the distance function used to measure the similarity, the description and retrieval efficiency of movement information can be increased. Through experiments, it was shown that the proposed method can describe movement information more efficiently and increase the retrieval efficiency compared to the previous method.

• Digital Contents
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• no.1 s.68
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• pp.22-27
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• 1999

전자 상거래 시대가 도래했다. IDC 리서치의 조사 결과에 의하면, 웹에서 이루어진 거래의 총액은 1996년에 26억 달러였던 것이 2001년이 되면 2000억 달러로 증가할 것이다. 그동안 기업의 웹 사이트를 그저 구경만 하는 정도에 지나지 않았던 사용자들도 웹에서 많은 돈을 쓰기 시작했다. 이러한 붐이 조성된 요인은 매력적인 웹 검색 도구들이 개발된 점과 '쇼핑로봇'이라고 하는 영리한 쇼핑 에이전트 덕분이다.

• Digital Contents
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• no.3 s.142
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• pp.102-105
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• 2005

온라인을 통해 각종 정보를 검색, 이용하는 온라인 DB서비스시장이 폭발적인 성장세를 구가하고 있다. 또 가입자 확대와 고기능 단말기 보급에 기댄 모바일 DB서비스가 새로운 DB서비스 시장의 견인차로 부상하며 DB시장 확대를 부추기고 있다. 한국데이터베이스진흥센터는 데이터베이스 산업의 지속적인 성장과 육성지원을 위한 발판을 마련하기 위해 2004년 국내 데이터베이스산업 현황조사를 실시했다.이 결과를 토대로 데이터베이스산업을 위한 정책이나 기업의 사업계획수립에 필요한 기초통계자료에 도움이 되길 바란다.

• Digital Contents
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• no.6 s.73
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• pp.42-43
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• 1999

한국전자거래협의회는 서치웨어라는 검색엔진을 도입해 전자상거래 분야에 특화된 'ec-net'을 개발했다. 정보통신부의 CALS/EC 사업과 연계해 국가적인 지식공유 기반으로서 전자상거래 동향, 전문인력, 기업기관, 구축 활용사례 등 다양한 전문정보를 제공하는 ec-net을 살펴봤다.

• Digital Contents
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• no.4 s.71
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• pp.40-43
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• 1999

디렉토리, 포틀(portals), 게이트웨이, 네비게이션 서비스, 이러한 명칭처럼 웹사이트에는 매주 새로운 것이 등장하고 있다. 모든 대형 회사들은 자신의 사이트를 직접 개설하거나 사이트의 한 구획을 사용하고 있다. 왜많은 기업들이 자신의 사이트를 가지려고 하겠는가? 1994년 스탠포드 대학 전자공학부에서 박사과정을 공부하던 두 사람이 인터넷상에서 자신들이 개인적으로 관심을 가졌던 것들의 경로를 기록하기 시작했기 때문이다. 이들의 목록은 Yahoo!(야후, Yet Another Hierarchical Officious Oracle)로 성장했다.

• Journal of Information Management
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• v.29 no.2
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• pp.1-17
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• 1998

The Inno-NET, which is based on the Internet and up-to-date information technology, is a consolidated system to provide business-related information and to solve the difficulties in business activities. In particular, the Inno-NET is an information system to integrate such business information for enterprise as start-up, financing, technology development, recruiting, site acquisition, marketing, trade and investment and so on, in order to help companies solve their problems and make up for their weak points. Accordingly, the Inno-NET will systematically connect supporting agencies and innovative enterprises, thus guaranteeing the exchange of information among them and coordinating the business. The supporting agencies will be included government offices, public organizations, research institutes, universities, and industrial associations all over the ministries. In short, Inno-NET forms a real-time decision making system among government, industries, universities and research institutes. by elt:ictronic networking on the Internet.

• Proceedings of the Korean Society of Computer Information Conference
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• 2016.01a
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• pp.167-168
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• 2016

2015년 대한민국을 관통하는 키워드 중 하나가 O2O (Online to Offline)이다. 대기업과 중소기업까지 O2O를 전면에 내세우고 새로운 비즈니스를 모색하는 기업들이 확대되고 있다. O2O 비즈니스 기업들의 업종도 모바일 메신저, 포털을 비롯한 인터넷 사업자, 통신사업자, 모바일 기기 제조사, 전자상거래 기업과 같은 정보통신기술(ICT) 관련 기업부터 유통기업까지 다양하다. 본 연구를 위하여 2014.5~2015.5 1년 간 여자대학생 92명의 '모바일 쇼핑 금융서비스 이용 현황' 조사를 실시하였다. 조사 결과, 상품정보검색(96.7%), 구매(88%), 주문 배송(77.2%), 할인 프로모션정보(62%) 등 모바일 쇼핑을 하였고, 모바일금융 서비스로는 하루에 1번정도 (20.4%), 월1~3회(20.4%), 1주 3~4회(16.3%), 이용 안하는 경우(24.5%)로 조사 되었다. 모바일 금융서비스를 이용하지 못하는 이유로는 개인정보보안 및 해킹우려(39%), 이용/결제 과정의 불편함(25.8%) 등 이었으며, 국내 O2O 플랫폼이 제공하는 서비스는 쇼핑부터 결제까지 완결적인 구조로 보완할 부분이 필수적이다.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.81-96
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• 2016

As the internet has become widespread and easy to access everywhere, it is common for people to search information via online search engines such as Google and Naver in everyday life. Recent studies have used online search volume of specific keyword as a measure of the internet users' attention in order to predict disease outbreaks such as flu and cancer, an unemployment rate, and an index of a nation's economic condition, and etc. For stock traders, web search is also one of major information resources to obtain data about individual stock items. Therefore, search volume of a stock item can reflect the amount of investors' attention on it. The investor attention has been regarded as a crucial factor influencing on stock price but it has been measured by indirect proxies such as market capitalization, trading volume, advertising expense, and etc. It has been theoretically and empirically proved that an increase of investors' attention on a stock item brings temporary increase of the stock price and the price recovers in the long run. Recent development of internet environment enables to measure the investor attention directly by the internet search volume of individual stock item, which has been used to show the attention-induced price pressure. Previous studies focus mainly on Dow Jones and NASDAQ market in the United States. In this paper, we investigate the relationship between the individual investors' attention measured by the internet search volumes and stock price changes of individual stock items in the KOSDAQ market in Korea, where the proportion of the trades by individual investors are about 90% of the total. In addition, we examine the difference between industries in the influence of investors' attention on stock return. The internet search volume of stocks were gathered from "Naver Trend" service weekly between January 2007 and June 2015. The regression model with the error term with AR(1) covariance structure is used to analyze the data since the weekly prices in a stock item are systematically correlated. The market capitalization, trading volume, the increment of trading volume, and the month in which each trade occurs are included in the model as control variables. The fitted model shows that an abnormal increase of search volume of a stock item has a positive influence on the stock return and the amount of the influence varies among the industry. The stock items in IT software, construction, and distribution industries have shown to be more influenced by the abnormally large internet search volume than the average across the industries. On the other hand, the stock items in IT hardware, manufacturing, entertainment, finance, and communication industries are less influenced by the abnormal search volume than the average. In order to verify price pressure caused by investors' attention in KOSDAQ, the stock return of the current week is modelled using the abnormal search volume observed one to four weeks ahead. On average, the abnormally large increment of the search volume increased the stock return of the current week and one week later, and it decreased the stock return in two and three weeks later. There is no significant relationship with the stock return after 4 weeks. This relationship differs among the industries. An abnormal search volume brings particularly severe price reversal on the stocks in the IT software industry, which are often to be targets of irrational investments by individual investors. An abnormal search volume caused less severe price reversal on the stocks in the manufacturing and IT hardware industries than on average across the industries. The price reversal was not observed in the communication, finance, entertainment, and transportation industries, which are known to be influenced largely by macro-economic factors such as oil price and currency exchange rate. The result of this study can be utilized to construct an intelligent trading system based on the big data gathered from web search engines, social network services, and internet communities. Particularly, the difference of price reversal effect between industries may provide useful information to make a portfolio and build an investment strategy.