• Journal of the Korean Society for Library and Information Science
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• v.24
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• pp.333-369
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• 1993

정보검색 시스템을 대하는 대부분의 이용자의 대답은 '이용하기에 어렵다'라는 것이다. 기계적인 정보검색을 기본 철학으로 하는 기존의 matching paradigm은 정보 곡체를 여기 저기 내용을 옮길 수 있는 물건으로 간주한다. 그리고 기존의 정보시스템은 이용자가 시스템을 구성한 사람의 의도 (즉, indexing, cataloguing rule)를 완전히 이해한다면, 즉 완전하게 질문식(query)을 작성한다면, 효과적인 검색을 할 수 있는 그런 시스템이다. 그러나 어느 이용자가 그 복잡한 시스템을 이해하고 정보검색을 할 수 있겠는가? 한마디로 시스템을 설계한 사람의 의도로 이용자가 적응해서 검색을 한다는 것은 아주 힘든 일이다. 그러나 우리가 이용자에 대한 인식을 다시 한다면 보다 나은 시스템을 만들 수 있다고 본다. 우리 인간은 아주 창조적이어서 자기가 처한 상황에서 이치에 맞게끔 자기 나름대로의 행동을 할 수 있다(sense-making approach). 이 사실을 인식한다면, 왜 이용자들의 행동양식에 시스템 설계자가 적응을 못하는 것인가? 하고 의문을 던질 수 있다. 앞으로의 시스템이 이용자들의 자연스러운 행동 패턴에 맞게 끔 설계된다면 기존의 시스템과 함께 쉽게 이용할 수 있는 편리한 시스템이 설계될 수 있을 것이다. 그러므로 도서관 및 정보학 연구에 있어서 기존의 분류. 목록에 대한 연구와 이용자체에 대한연구(예를 들면, 몇 시에 이용자가 많은가? 어떤 종류의 책을 어떤 계충에서 많이 보는가? 도서 및 잡지가 어떻게 양적으로 성장해 왔는가? 등등의 use study)와 함께 여기서 제시한 제3의 요소인 이용자의 인식(cognition)을 시스템설계에 반드시 도입을 해야만 한다고 본다(user-centric approach). 즉 이용자를 중간 중간에서 도울 수 있는 facilitator가 많이 제공되어야 한다. 이용자의 다양한 패턴의 정보요구(information needs)에 부응할 수 있고, 질문식(query)을 잘 만들 수 없는 이용자를 도울 수 있고(ASK hypothesis: Anomolous State of Knowledge), 어떤 질문식 없이도 자유스럽게 Browsing할 수 있는(예를 들면 hypertext) 시스템을 설계하기 위해서는 눈에 보이는 이용자의 행동패턴(external behavior)도 중요하지만 우리 눈에는 보이지 않는 이용자의 심리상태를 이해한다면 훨씬 나은 시스템을 만들 수 있다. 이용자가 '왜?' '어떤 상황에서,' '어떤 목적으로,' '어떻게,' 정보를 검색하는지에 대해서 새로운 관심을 들려서 이용자들이 얼마나 우리 시스템 설계자들의 의도에 미치지 못한다는 사실을 인식 해야한다. 이 분야의 연구를 위해서는 새로운 paradigm이 필수적으로 필요하다고 본다. 단지 'user-study'만으로는 부족하며 새로운 시각으로 이용자를 연구해야 한다. 가령 새롭게 설치된 computer-assisted system에서 이용자들이 어떻게, 그리핀 어떤 분야에서 왜 그렇게 오류 (error)를 범하는지 분석한다면 앞으로의 computer 시스템 선계에 큰 도움을 줄 수 있을 것으로 믿는다. 실제로 많은 방법이 개발되고 있다. 그러면 시스템 설계자가 가졌던 이용자들이 이러 이러한 방식으로 정보검색을 할 것이라는 예측과(즉, conceptual model) 실제 이용자들이 정보검색을 할 때 일어나는 행동패턴 사이에는(즉, mental model) 상당한 차이점이 있다는 것을 알게 될 것이다. 이 차이점을 줄이는 것이 시스템 설계자의 의무라고 생각한다. 결론적으로, Computer에 대한 새로운 지식과 함께 이용자들의 인식을 연구할 수 있는, 철학적이고 방법론적인 연구를 계속하나가면서, 이용자들의 행동패턴을 어떻게 시스템 설계에 적용할 수 있는 지를 연구해야 한다. 중요하게 인식해야할 사실은 구 Paradigm을 완전히 무시하라는 것은 아니고 단지 이용자에 대한 새로운 인식을 추가하자는 것이다. 그것이 진정한 User Study가 될 수 있는 길이라고 생각하며, 컴퓨터와 이용자 사이의 '원활한 의사교환'이 필수불가결 한 지금 우리 학문이 가야 할 한 연구분야이다. (Human Interaction with Computers)

• Journal of KIISE:Databases
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• v.34 no.3
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• pp.179-192
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• 2007

This paper addresses an approach that recommends investment types for stock investors by discovering useful rules from past changing patterns of stock prices in databases. First, we define a new rule model for recommending stock investment types. For a frequent pattern of stock prices, if its subsequent stock prices are matched to a condition of an investor, the model recommends a corresponding investment type for this stock. The frequent pattern is regarded as a rule head, and the subsequent part a rule body. We observed that the conditions on rule bodies are quite different depending on dispositions of investors while rule heads are independent of characteristics of investors in most cases. With this observation, we propose a new method that discovers and stores only the rule heads rather than the whole rules in a rule discovery process. This allows investors to define various conditions on rule bodies flexibly, and also improves the performance of a rule discovery process by reducing the number of rules. For efficient discovery and matching of rules, we propose methods for discovering frequent patterns, constructing a frequent pattern base, and indexing them. We also suggest a method that finds the rules matched to a query issued by an investor from a frequent pattern base, and a method that recommends an investment type using the rules. Finally, we verify the superiority of our approach via various experiments using real-life stock data.

• Journal of Korean Tunnelling and Underground Space Association
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• v.15 no.5
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• pp.505-522
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• 2013

Previously, a new concept of indexing methodology has been proposed for quantitative assessment of tunnel collapse hazard level at each tunnel face with respect to the given geological data, design condition and the corresponding construction activity (Shin et al, 2009a). In this paper, 'linear' model, in which weights of influence factors are invariable, and 'non-linear' model, in which weights of influence factors are variable, are taken into account with some examples. Then, the 'non-linear' model is validated by using 100 tunnel collapse cases. It appears that 'non-linear' model allows us to have adapted weight values of influence factors to characteristics of given tunnel site. In order to make a better understanding and help for an effective use of the system, a series of operating processes of the system are built up. Then, by following the processes, the system is applied to a real-life tunnel project in very weak and varying ground conditions. Through this approach, it would be quite apparent that the tunnel collapse hazard indices are determined by well interlinked consideration of face mapping data as well as design/construction data. The calculated indices seem to be in good agreement with available electric resistivity distribution and design/construction status. In addition, This approach could enhance effective usage of face mapping data and lead timely and well corresponding field reactions to situation of weak tunnel faces.

• Journal of the Mineralogical Society of Korea
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• v.24 no.1
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• pp.43-53
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• 2011

Health risk assessments for the abandoned asbestos mine were usually performed with activity-based sampling (ABS) method, which was not a effective tool for indexing health risk on an exact small area of mine. A newly proposed potential index of health risk (PIHR) was applied with proper spatial determination of geographical information system (GIS) to assess quantitatively health risks. A new trial was applied to a certain abandoned mine in Boryong as follows: A high grade area of PIHR was estimated 7.8% of the whole area of the mine (about 27.3 ha). Based on US EPA IRIS (integrated risk information system) model considering lifetime excess cancer risk (LECR), the health risk assessment indicated that the high grade area increased from 3.0 ha through 12.9 ha to 19.5 ha with an increase of asbestos contents in soil from 0.36% (1E-04 level) through 0.1% (3E-05 level) to 0.04% (1E-05 level). These results can be effectively applied to determine reclamation area of the abandoned asbestos mine.

• Journal of KIISE:Software and Applications
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• v.26 no.10
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• pp.1204-1218
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• 1999

문서영상 검색을 위한 디지털도서관의 대부분은 논문제목과/또는 논문요약으로부터 만들어진 색인에 근거한 제한적인 검색기능을 제공하고 있다. 본 논문에서는 영문 문서영상전체에 대한 검색을 위한 단어 영상 형태 특징기반의 단어검색시스템을 제안한다. 본 논문에서는 검색의 효율성과 정확도를 높이기 위해 1) 기존의 단어검색시스템에서 사용된 특징들을 조합하여 사용하며, 2) 특징의 개수 및 위치뿐만 아니라 특징들의 순서를 포함하여 매칭하는 방법을 사용하며, 3) 특징비교에 의해 검색결과를 얻은 후에 여과목적으로 문자인식을 부분적으로 적용하는 2단계의 검색방법을 사용한다. 제안된 시스템의 동작은 다음과 같다. 문서 영상이 주어지면, 문서 영상 구조가 분석되고 단어 영역들의 조합으로 분할된다. 단어 영상의 특징들이 추출되어 저장된다. 사용자의 텍스트 질의가 주어지면 이에 대응되는 단어 영상이 만들어지며 이로부터 영상특징이 추출된다. 이 참조 특징과 저장된 특징들과 비교하여 유사한 단어를 검색하게 된다. 제안된 시스템은 IBM-PC를 이용한 웹 환경에서 구축되었으며, 영문 문서영상을 이용하여 실험이 수행되었다. 실험결과는 본 논문에서 제안하는 방법들의 유효성을 보여주고 있다. Abstract Most existing digital libraries for document image retrieval provide a limited retrieval service due to their indexing from document titles and/or the content of document abstracts. This paper proposes a word spotting system for full English document image retrieval based on word image shape features. In order to improve not only the efficiency but also the precision of a retrieval system, we develop the system by 1) using a combination of the holistic features which have been used in the existing word spotting systems, 2) performing image matching by comparing the order of features in a word in addition to the number of features and their positions, and 3) adopting 2 stage retrieval strategies by obtaining retrieval results by image feature matching and applying OCR(Optical Charater Recognition) partly to the results for filtering purpose. The proposed system operates as follows: given a document image, its structure is analyzed and is segmented into a set of word regions. Then, word shape features are extracted and stored. Given a user's query with text, features are extracted after its corresponding word image is generated. This reference model is compared with the stored features to find out similar words. The proposed system is implemented with IBM-PC in a web environment and its experiments are performed with English document images. Experimental results show the effectiveness of the proposed methods.

• The KIPS Transactions:PartA
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• v.17A no.5
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• pp.229-236
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• 2010

With an increasing number of documents in the Internet or enterprises, it becomes crucial to efficiently support users' queries on those documents. In that situation, the full-text search technique is accepted in general, because it can answer uncontrolled ad-hoc queries by automatically indexing all the keywords found in the documents. The size of index files made for full-text searches grows with the increasing number of indexed documents, and thus the disk cost may be too large to process multi-keyword queries against those enlarged index files. To solve the problem, we propose both of the index file structure and its management scheme suitable to the processing of multi-keyword queries against a large volume of index files. For this, we adopt the structure of inverted-files, which are widely used in the multi-keyword searches, as a basic index structure and modify it to a hierarchical structure for join operations and ranking operations performed during the query processing. In order to save disk costs based on that index structure, we dynamically store in the main memory the results of join operations between two keywords, if they are highly expected to be entered in users' queries. We also do performance comparisons using a cost model of the disk to show the performance advantage of the proposed scheme.

• Journal of Korean Library and Information Science Society
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• v.52 no.2
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• pp.235-252
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• 2021

As part of effort to develop the strategies of internationalization of social science academic journals in South Korea, this study attempts to verify the measurement invariance of journal selection criteria across the groups of library and information science researchers and social science researchers. The authors collected 146 survey responses from researchers who have published at least one paper in SSCI/Scopus-indexed social science journals between 2014 and 2016. As a result of the study, it was found that the configural and partial metric invariance of the journal selection criteria held across the two groups, implying that the model of journal selection criteria is appropriate to use in the field of social science as well as library and information science. Additionally, the authors investigated the perceptions of journal selection criteria indicators in the two groups, and it was shown that researchers in both groups considered peer review and indexing in major databases important. The findings of this study could be useful for publishers or academic societies to develop improvement strategies of their journals.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.143-156
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• 2012

People easily believe that news and stock index are closely related. They think that securing news before anyone else can help them forecast the stock prices and enjoy great profit, or perhaps capture the investment opportunity. However, it is no easy feat to determine to what extent the two are related, come up with the investment decision based on news, or find out such investment information is valid. If the significance of news and its impact on the stock market are analyzed, it will be possible to extract the information that can assist the investment decisions. The reality however is that the world is inundated with a massive wave of news in real time. And news is not patterned text. This study suggests the stock-index invest model based on "News Big Data" opinion mining that systematically collects, categorizes and analyzes the news and creates investment information. To verify the validity of the model, the relationship between the result of news opinion mining and stock-index was empirically analyzed by using statistics. Steps in the mining that converts news into information for investment decision making, are as follows. First, it is indexing information of news after getting a supply of news from news provider that collects news on real-time basis. Not only contents of news but also various information such as media, time, and news type and so on are collected and classified, and then are reworked as variable from which investment decision making can be inferred. Next step is to derive word that can judge polarity by separating text of news contents into morpheme, and to tag positive/negative polarity of each word by comparing this with sentimental dictionary. Third, positive/negative polarity of news is judged by using indexed classification information and scoring rule, and then final investment decision making information is derived according to daily scoring criteria. For this study, KOSPI index and its fluctuation range has been collected for 63 days that stock market was open during 3 months from July 2011 to September in Korea Exchange, and news data was collected by parsing 766 articles of economic news media M company on web page among article carried on stock information>news>main news of portal site Naver.com. In change of the price index of stocks during 3 months, it rose on 33 days and fell on 30 days, and news contents included 197 news articles before opening of stock market, 385 news articles during the session, 184 news articles after closing of market. Results of mining of collected news contents and of comparison with stock price showed that positive/negative opinion of news contents had significant relation with stock price, and change of the price index of stocks could be better explained in case of applying news opinion by deriving in positive/negative ratio instead of judging between simplified positive and negative opinion. And in order to check whether news had an effect on fluctuation of stock price, or at least went ahead of fluctuation of stock price, in the results that change of stock price was compared only with news happening before opening of stock market, it was verified to be statistically significant as well. In addition, because news contained various type and information such as social, economic, and overseas news, and corporate earnings, the present condition of type of industry, market outlook, the present condition of market and so on, it was expected that influence on stock market or significance of the relation would be different according to the type of news, and therefore each type of news was compared with fluctuation of stock price, and the results showed that market condition, outlook, and overseas news was the most useful to explain fluctuation of news. On the contrary, news about individual company was not statistically significant, but opinion mining value showed tendency opposite to stock price, and the reason can be thought to be the appearance of promotional and planned news for preventing stock price from falling. Finally, multiple regression analysis and logistic regression analysis was carried out in order to derive function of investment decision making on the basis of relation between positive/negative opinion of news and stock price, and the results showed that regression equation using variable of market conditions, outlook, and overseas news before opening of stock market was statistically significant, and classification accuracy of logistic regression accuracy results was shown to be 70.0% in rise of stock price, 78.8% in fall of stock price, and 74.6% on average. This study first analyzed relation between news and stock price through analyzing and quantifying sensitivity of atypical news contents by using opinion mining among big data analysis techniques, and furthermore, proposed and verified smart investment decision making model that could systematically carry out opinion mining and derive and support investment information. This shows that news can be used as variable to predict the price index of stocks for investment, and it is expected the model can be used as real investment support system if it is implemented as system and verified in the future.

• KDI Journal of Economic Policy
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• v.13 no.1
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• pp.115-134
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• 1991

The role of pension plans in the macroeconomy has been a subject of much interest for some years. It has come to be recognized that pension plans may alter basic macroeconomic behavior patterns. The net effects on both savings and labor supply are thus matters for speculation. The aim of the present paper is to provide quantitative results which may be helpful in attaching orders of magnitude to some of the possible effects. We are not concerned with the providing empirical evidence relating to actual behavior, but rather with deriving the macroeconomic implications for a alternative possibilities. The pension plan interacts with the economy and the population in a number of ways. Demographic variables may thus affect both the economic burden of a national pension plan and the ability of the economy to sustain the burden. The tax transfer process associated with the pension plan may have implications for national patterns of saving and consumption. The existence of a pension plan may have implications also for the size of the labor force, inasmuch as labor force participation rates may be affected. Changes in technology and the associated changes in average productivity levels bear directly on the size of the national income, and hence on the pension contribution base. The vehicle for the analysis is a hypothetical but broadly realistic simulation model of an economic- demographic system into which is inserted a national pension plan. All income, expenditure, and related aggregates are in real terms. The economy is basically neoclassical; full employment is assumed, output is generated by a Cobb-Douglas production process, and factors receive their marginal products. The model was designed for use in computer simulation experiments. The simulation results suggest a number of general conclusions. These may be summarized as follows; - The introduction of a national pension plan (funded system) tends to increase the rate of economic growth until cost exceeds revenue. - A scheme with full wage indexing is more expensive than one in which pensions are merely price indexed. - The rate of technical progress is not a critical element in determining the economic burden of the pension scheme. - Raising the rate of benefits affects its economic burden, and raising the age of eligibility may decrease the burden substantially. - The level of fertility is an element in determining the long-run burden. A sustained low fertility rate increases the proportion of the aged in total population and increases the burden of the pension plan. High fertility has inverse effects.