• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2001.05a
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• pp.105-106
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• 2001

일반적인 정보 검색은 색인어를 통해 이루어지는데 이런 경우 사용자는 정보를 검색하기 위해 데이터베이스에 저장된 정보들이 가지고 있는 색인어를 정확하게 입력해야 한다. 그러나 일반 사용자가 색인어를 정확하게 입력하기는 어렵고, 특히 찾고자 하는 분야가 전문 분야에서 사용되는 용어일 때는 더욱 그러하다. 이럴 때 시소러스와 같은 지식구조를 이용해서 색인어를 탐색하여 검색의 효율을 높일 수 있다. 최근 들어 정보기술 분야의 연구가 활발함에 따라 정보자로의 생산이 급격히 증가하고 이를 관련 주제 분야의 연구정보로 활용하는 경우가 증가하고 있다. 따라서 IT 분야의 정보를 관리할 수 있는 시스템의 개발이 시급하다. 또한 IT 분야와 같은 전문분야일 때 검색 시스템에서 사용할 용어의 관리에 대한 연구의 필요성이 증가하고 있다. 본 논문에서는 IT분야의 정보를 검색할 수 있는 IT 업체정보검색시스템에서 정보 검색시에 생기는 용어간의 불일치 문제를 해결하고, 각 용어들간의 계층 관계를 나타내어 정보 검색시 검색어의 확장을 도울 수 있는 용어 관리 시스템의 구조를 제안하고 그에 대한 검색 알고리즘을 제시한다. 제안된 구조는 사용자의 검색어에 대한 동의어 관계나 상위어, 하위어 등의 계층 관계를 파악하여 검색의 범위에 추가함으로써 검색 효율을 높일 수 있다. 또한 새로운 용어의 생성이나 삭제와 같은 연산이 발생했을 때 시스템을 동적으로 확장할 수 있도록 구현하였다. 제안된 시스템은 단어간의 계층 구조를 효율적으로 검색하기 위하여 객체-관계형 데이터베이스를 사용하였다. 또한 메모리 상주 DBMS를 사용하여 많은 사용자들이 동시에 접근하는 환경에서도 빠른 검색 성능을 유지할 수 있도록 하였다. 제시된 방법은 정보기술 분야뿐만 아니라 다른 전문용어 분야의 연구로도 그 범위를 확장 할 수 있다.자기자본비용의 조합인 기회자본비용으로 할인함으로써 현재의 기업가치를 구할 수 있기 때문이다. 이처럼 기업이 영업활동이나 투자활동을 통해 현금을 창출하고 소비하는 경향은 해당 비즈니스 모델의 성격을 규정하는 자료도로 이용될 수 있다. 또한 최근 인터넷기업들의 부도가 발생하고 있는데, 기업의 부실원인이 어떤 것이든 사회전체의 생산력의 감소, 실업의 증가, 채권자 및 주주의 부의 감소, 심리적 불안으로 인한 경제활동의 위축, 기업 노하우의 소멸, 대외적 신용도의 하락 등과 같은 사회적·경제적 파급효과는 대단히 크다. 이상과 같은 기업부실의 효과를 고려할 때 부실기업을 미리 예측하는 일종의 조기경보장치를 갖는다는 것은 중요한 일이다. 현금흐름정보를 이용하여 기업의 부실을 예측하면 기업의 부실징후를 파악하는데 그치지 않고 부실의 원인을 파악하고 이에 대한 대응 전략을 수립하며 그 결과를 측정하는데 활용될 수도 있다. 따라서 본 연구에서는 기업의 부도예측 정보 중 현금흐름정보를 통하여 '인터넷기업의 미래 현금흐름측정, 부도예측신호효과, 부실원인파악, 비즈니스 모델의 성격규정 등을 할 수 있는가'를 검증하려고 한다. 협력체계 확립, ${\circled}3$ 전문인력 확보 및 인력구성 조정, 그리고 ${\circled}4$ 방문보건사업의 강화 등이다., 대사(代謝)와 관계(關係)있음을 시사(示唆)해 주고 있다.ble nutrient (TDN) was highest in booting stage (59.7%); however no significant difference was found among other stages. The concentrations of Ca and P were not different among mature stages. Accordi

• The Journal of the Korea Contents Association
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• v.20 no.8
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• pp.499-512
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• 2020

The development of the economy and network environment has a great impact on physical stores, and physical bookstores are gradually upgrading and transforming with the pace of the times. This study takes the modern bookstore under the concept of the third space as the research object. The purpose of it is to understand the needs of consumers for the space of the modern bookstores, explore the characteristics and development direction of them, which provides theoretical guidance for the follow-up development of the modern bookstore. Based on the concept of the third space and the theory of lifestyle shops and reorganizing theoretical investigation and prior research, the researcher extracts the characteristic elements of modern bookstores in line with the concept of the third space. Moreover, the research analyzes five bookstores opened in large-scale commercial facilities after 2010 as research cases. Through the analysis of the results, it shows that the modern bookstore is a multi-functional and compounded space which is gradually transformed from a single bookseller to a seller of selling lifestyle proposal. And through the analysis of big data to predict the changes in market consumption, we can find out the different needs of consumers, so as to carry out the targeted design of bookstore space and then improve the value of it. In the context of the co-development of economy and culture, the transformation of modern bookstores actually conforms to the change of consumer demand and realizes a virtuous circle.

• Korean Journal of Social Welfare
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• v.69 no.4
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• pp.41-65
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• 2017

This study aimed to examine the social transition, which is often metaphorized as the Fourth Industrial Revolution, within the context of social work practice and to explore measures to improve social work practice in such transition. Four social welfare researchers held seven discussions to predict the social changes in the near future centered on the Fourth Industrial Revolution and find the corresponding development strategies in social work practice; collective autobiography method was used to analyze the discussion. The analysis ascertained hyper connectivity, the advent and expansion of new communities, diversification and individualization, and the emergence of new criteria for the assessment of one's quality of life as the distinctive qualities of the near future. It was analyzed that humans and organic materials will be interconnected through spatial and temporal transcendence and that humans liberated from labor will seek for diverse communities while the number of atomized individual will increase simultaneously. Furthermore, the rise of new order of life accompanied by both the expansion of diversification and individualization and the ecological worldview brought forth by post materialistic trend was predicted. Meanwhile, the disengagement from macroscopic context, a biased inclination towards technique orientated professionalism, and individualistic social work practices without integrity were identified as the limitations of the current social work practice. This study presented three goals for social work practice to help it overcome its current shortcomings and correspond to the social changes: first, the rearrangement of practice knowledge, technique, and value so that it is based on humans and society, which are the essence of social practice work; second, the practice, such as sharing economy, that expands the individuals' boundaries of life to the community; three, the restoration of the desirability of professional social works by examining its special nature.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.155-175
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• 2017

As social data become into the spotlight, mainstream web search engines provide data indicate how many people searched specific keyword: Web Search Traffic data. Web search traffic information is collection of each crowd that search for specific keyword. In a various area, web search traffic can be used as one of useful variables that represent the attention of common users on specific interests. A lot of studies uses web search traffic data to nowcast or forecast social phenomenon such as epidemic prediction, consumer pattern analysis, product life cycle, financial invest modeling and so on. Also web search traffic data have begun to be applied to predict tourist inbound. Proper demand prediction is needed because tourism is high value-added industry as increasing employment and foreign exchange. Among those tourists, especially Chinese tourists: Youke is continuously growing nowadays, Youke has been largest tourist inbound of Korea tourism for many years and tourism profits per one Youke as well. It is important that research into proper demand prediction approaches of Youke in both public and private sector. Accurate tourism demands prediction is important to efficient decision making in a limited resource. This study suggests improved model that reflects latest issue of society by presented the attention from group of individual. Trip abroad is generally high-involvement activity so that potential tourists likely deep into searching for information about their own trip. Web search traffic data presents tourists' attention in the process of preparation their journey instantaneous and dynamic way. So that this study attempted select key words that potential Chinese tourists likely searched out internet. Baidu-Chinese biggest web search engine that share over 80%- provides users with accessing to web search traffic data. Qualitative interview with potential tourists helps us to understand the information search behavior before a trip and identify the keywords for this study. Selected key words of web search traffic are categorized by how much directly related to "Korean Tourism" in a three levels. Classifying categories helps to find out which keyword can explain Youke inbound demands from close one to far one as distance of category. Web search traffic data of each key words gathered by web crawler developed to crawling web search data onto Baidu Index. Using automatically gathered variable data, linear model is designed by multiple regression analysis for suitable for operational application of decision and policy making because of easiness to explanation about variables' effective relationship. After regression linear models have composed, comparing with model composed traditional variables and model additional input web search traffic data variables to traditional model has conducted by significance and R squared. after comparing performance of models, final model is composed. Final regression model has improved explanation and advantage of real-time immediacy and convenience than traditional model. Furthermore, this study demonstrates system intuitively visualized to general use -Youke Mining solution has several functions of tourist decision making including embed final regression model. Youke Mining solution has algorithm based on data science and well-designed simple interface. In the end this research suggests three significant meanings on theoretical, practical and political aspects. Theoretically, Youke Mining system and the model in this research are the first step on the Youke inbound prediction using interactive and instant variable: web search traffic information represents tourists' attention while prepare their trip. Baidu web search traffic data has more than 80% of web search engine market. Practically, Baidu data could represent attention of the potential tourists who prepare their own tour as real-time. Finally, in political way, designed Chinese tourist demands prediction model based on web search traffic can be used to tourism decision making for efficient managing of resource and optimizing opportunity for successful policy.