• Title/Summary/Keyword: 시소러스 관리

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IT 업체정보검색시스템에서 동의어 처리 기법

  • 강옥선;이현철;조완섭
    • 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

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An Investigation of the Objectiveness of Image Indexing from Users' Perspectives (이용자 관점에서 본 이미지 색인의 객관성에 대한 연구)

  • 이지연
    • Journal of the Korean Society for information Management
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    • v.19 no.3
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    • pp.123-143
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    • 2002
  • Developing good methods for image description and indexing is fundamental for successful image retrieval, regardless of the content of images. Researchers and practitioners in the field of image indexing have developed a variety of image indexing systems and methods with the consideration of information types delivered by images. Such efforts in developing image indexing systems and methods include Panofsky's levels of image indexing and indexing systems adopting different approaches such as thesauri-based approach, classification approach. description element-based approach, and categorization approach. This study investigated users' perception of the objectiveness of image indexing, especially the iconographical analysis of image information advocated by Panofsky. One of the best examples of subjectiveness and conditional-dependence of image information is emotion. As a result, this study dealt with visual emotional information. Experiments were conducted in two phases : one was to measure the degree of agreement or disagreement about the emotional content of pictures among forty-eight participants and the other was to examine the inter-rater consistency defined as the degree of users' agreement on indexing. The results showed that the experiment participants made fairly subjective interpretation when they were viewing pictures. It was also found that the subjective interpretation made by the participants resulted from the individual differences in terms of their educational or cultural background. The study results emphasize the importance of developing new ways of indexing and/or searching for images, which can alleviate the limitations of access to images due to the subjective interpretation made by different users.

A Study on the Use of Criminal Justice Information Big Data in terms of the Structuralization and Categorization (형사사법정보의 빅데이터 활용방안 연구: 구조화 범주화 관점으로)

  • Kim, Mi Ryung;Roh, Yoon Ju;Kim, Seonghun
    • Journal of the Korean Society for information Management
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    • v.36 no.4
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    • pp.253-277
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    • 2019
  • In the era of the 4th Industrial Revolution, the importance of data is intensifying, but there are many cases where it is not easy to use data due to personal information protection. Although criminal justice information is expected to have various useful values such as crime prediction and prevention, scientific investigation of criminal investigations, and rationalization of sentencing, the use of criminal justice information is currently limited as a matter of legal interpretation related to privacy protection and criminal justice information. This study proposed to convert criminal justice information into 'crime data' and use it as big data through the structuralization and categorization of criminal justice information. And when using "crime data," legal issues, value in use, considerations for data generation and use were verified by experts, and future strategic development plans were identified. Finally we found that 'crime data' seems to have solved the privacy problem, but it is necessary to specify in the criminal justice information related law and it is urgent to be organized in a standardized form for analysis to use big data. Future directions are to derive data elements, construct a dictionary thesaurus, define and classify personal sensitive information for data grading, and develop algorithms for shaping unstructured data.

ISAAC : An Integrated System with User Interface for Sentence Analysis (ISAAC :문장분석용 통합시스템 및 사용자 인터페이스)

  • Kim, Gon;Kim, Min-Chan;Bae, Jae-Hak;Lee, Jong-Hyuk
    • The KIPS Transactions:PartB
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    • v.11B no.1
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    • pp.107-116
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    • 2004
  • This paper introduces ISAAC (An Interface for Sentence Analysis & Abstraction with Cogitation) which provides an integrated user interface for sentence analysis. Into ISAAC, the various linguistic tools and resources are integrated. They are necessary for sentence analysis. Most of the tools and resources for sentence analysis are developed and accumulated independently. In the sentence analyzing with these tools and resources, it is difficult for sentence analyst to manage and control information which is taken on each step. In this respect, we have integrated the usable tools and resources, and made ISAAC to provide the consistent user oriented interface to each function. We have been able to divide sentence analysis process Into 14 steps. In ISAAC, these steps are processed by four individual modules $\cicled1$syntactic analysis of sentence,$\cicled2$retrieval of a root word,$\cicled3$searching category information in Roget s Thesaurus, and $\cicled4$searching category information in OfN(Ontology for Narratives). Therefore, in case of sentence analysis with ISAAC, the process of total 14 steps falls into 4 steps. This means that it is able to improve the performance of sentence analyst to the extent 3.5 times or more. Furthermore, ISAAC undertaking tedious transcription needed to process each step, we expect that ISAAC can help the analyst to maintain the accuracy of sentence analysis.

Term Mapping Methodology between Everyday Words and Legal Terms for Law Information Search System (법령정보 검색을 위한 생활용어와 법률용어 간의 대응관계 탐색 방법론)

  • Kim, Ji Hyun;Lee, Jong-Seo;Lee, Myungjin;Kim, Wooju;Hong, June Seok
    • Journal of Intelligence and Information Systems
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    • v.18 no.3
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    • pp.137-152
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    • 2012
  • In the generation of Web 2.0, as many users start to make lots of web contents called user created contents by themselves, the World Wide Web is overflowing by countless information. Therefore, it becomes the key to find out meaningful information among lots of resources. Nowadays, the information retrieval is the most important thing throughout the whole field and several types of search services are developed and widely used in various fields to retrieve information that user really wants. Especially, the legal information search is one of the indispensable services in order to provide people with their convenience through searching the law necessary to their present situation as a channel getting knowledge about it. The Office of Legislation in Korea provides the Korean Law Information portal service to search the law information such as legislation, administrative rule, and judicial precedent from 2009, so people can conveniently find information related to the law. However, this service has limitation because the recent technology for search engine basically returns documents depending on whether the query is included in it or not as a search result. Therefore, it is really difficult to retrieve information related the law for general users who are not familiar with legal terms in the search engine using simple matching of keywords in spite of those kinds of efforts of the Office of Legislation in Korea, because there is a huge divergence between everyday words and legal terms which are especially from Chinese words. Generally, people try to access the law information using everyday words, so they have a difficulty to get the result that they exactly want. In this paper, we propose a term mapping methodology between everyday words and legal terms for general users who don't have sufficient background about legal terms, and we develop a search service that can provide the search results of law information from everyday words. This will be able to search the law information accurately without the knowledge of legal terminology. In other words, our research goal is to make a law information search system that general users are able to retrieval the law information with everyday words. First, this paper takes advantage of tags of internet blogs using the concept for collective intelligence to find out the term mapping relationship between everyday words and legal terms. In order to achieve our goal, we collect tags related to an everyday word from web blog posts. Generally, people add a non-hierarchical keyword or term like a synonym, especially called tag, in order to describe, classify, and manage their posts when they make any post in the internet blog. Second, the collected tags are clustered through the cluster analysis method, K-means. Then, we find a mapping relationship between an everyday word and a legal term using our estimation measure to select the fittest one that can match with an everyday word. Selected legal terms are given the definite relationship, and the relations between everyday words and legal terms are described using SKOS that is an ontology to describe the knowledge related to thesauri, classification schemes, taxonomies, and subject-heading. Thus, based on proposed mapping and searching methodologies, our legal information search system finds out a legal term mapped with user query and retrieves law information using a matched legal term, if users try to retrieve law information using an everyday word. Therefore, from our research, users can get exact results even if they do not have the knowledge related to legal terms. As a result of our research, we expect that general users who don't have professional legal background can conveniently and efficiently retrieve the legal information using everyday words.