• Title/Summary/Keyword: 조직화

Search Result 1,387, Processing Time 0.026 seconds

A Study on Information Organization Methods for Digital Library -Focused on Administrative Metadata- (디지털도서관의 정보조직화 방안 연구 -관리적 메타데이터를 중심으로-)

  • 이종문
    • Journal of Korean Library and Information Science Society
    • /
    • v.35 no.1
    • /
    • pp.319-335
    • /
    • 2004
  • This paper suggests how to systemize administrative metadata required for managing intellectual property rights and their applications, which has been newly requested in digital library environment. For this purpose, firstly, the types of metadata required in digital libraries were identified. Secondly, this paper detected problems in MARC that digital libraries have been using as the tool for information organization. Finally, the structures of administrative metadata required by copyright laws were analyzed. On the basis of the researches above, this paper proposed how to systemize and operate administrative metadata that interlocks MARC, Dublin Core and administrative system of copyright trust agencies.

  • PDF

Clustering of Gene Expression Data by using SOM and Hierarchical Clustering (자기 조직화 지도와 계층적 군집화를 이용한 유전자 발현 데이터 군집화 기법)

  • 박창범;이동환;이성환
    • Proceedings of the Korean Information Science Society Conference
    • /
    • 2003.10b
    • /
    • pp.784-786
    • /
    • 2003
  • 본 논문에서는 유전자 발현 데이터를 분석하는데 있어서 자기 조직화 지도와 계층적 군집화 기법을 상호 보완적으로 사용하여 사용자가 보다 직관적으로 군집화 결과를 해석할 수 있는 방법을 제안한다. 제안된 방법을 사용하면 빠른 처리 속도로 대용량 데이터 처리에 적합한 자기 조직화 지도의 장점을 살릴 수 있으며 계층적 군집화의 장점인 가시화 기능을 이용하여 자기 조직화 지도의 단점인 군집 경계에 대한 불명확성을 해소하여 군집화 결과를 사용자가 쉽게 이해하고 직관적으로 해석할 수 있도록 도와준다. 본 논문에서 제안된 방법의 효용성을 검증하기 위해 세 종류의 데이터를 사용하여 실험을 수행한 결과 제안된 방법이 기존 방법에 비해 더 나은 성능을 보이는 것을 확인할 수 있었다.

  • PDF

Distributed controllers using a Self-Organizing Map Neural Network in SDN environment (SDN 환경에서 자기조직화지도 신경망을 이용한 분산 컨트롤러)

  • Yoo, Seung-Eon;Kim, Min-Woo;Lee, Byung-Jun;Kim, Kyung-Tae;Youn, Hee-Yong
    • Proceedings of the Korean Society of Computer Information Conference
    • /
    • 2019.01a
    • /
    • pp.47-48
    • /
    • 2019
  • 본 논문에서는 신경망의 일종인 자기조직화지도(Self Organizing Map)을 이용하여 컨트롤러의 순서를 정하는 모델을 제안하였다. 자기조직화지도는 자율 학습에 의한 클러스터링을 수행하는 알고리즘으로써 컨트롤러에 가중치를 부여하고 컨트롤러 간 거리를 계산하여 효율적인 컨트롤러 선택을 목표로 한다.

  • PDF

Micro Enterprise Policy to Reduce Trade Conflict Due to SSM Enter Restriction : An Empirical Analysis on the Determinants of Micro Enterprise Organization (SSM 진출규제에 따른 국제통상마찰 완화를 위한 소상공인 정책방향 : 소상공인 조직화 결정요인 실증분석)

  • Jun, In-Woo;Moon, Sun-Ung
    • International Commerce and Information Review
    • /
    • v.13 no.1
    • /
    • pp.245-270
    • /
    • 2011
  • It is known that weak competitiveness of micro enterprises can be overcome when they are organized with enterprise associations, franchise systems, and joint affiliation. In this paper, we empirically analyze the determinants of organization of micro enterprises, and propose the policy implementations to enhance the competitiveness of micro enterprises as a measure to reduce trade conflict due to SSM entry restrictions. Logit estimation results based on survey data consisted of 467 samples, show that insufficient labor force and high material costs had negative effects on organization. The unexpected findings generally support the rationale that organization is not helpful to solve insufficient labor force and high material costs. However, the decrease in sales due to the economic recession and the decreasing number of customers due to customer transition to large enterprises had a more positive effect on organization than usually expected. There are differences in estimation results between two types of business(restaurants and retail). In case of the restaurant business, insufficient labor force, high material costs and a decreasing of number of customers are important factors for organization, while the sales decrease is a relatively important factor in the case of retail businesses.

  • PDF

SOM-Based $R^{*}-Tree$ for Similarity Retrieval (자기 조직화 맵 기반 유사 검색 시스템)

  • O, Chang-Yun;Im, Dong-Ju;O, Gun-Seok;Bae, Sang-Hyeon
    • The KIPS Transactions:PartD
    • /
    • v.8D no.5
    • /
    • pp.507-512
    • /
    • 2001
  • Feature-based similarity has become an important research issue in multimedia database systems. The features of multimedia data are useful for discriminating between multimedia objects. the performance of conventional multidimensional data structures tends to deteriorate as the number of dimensions of feature vectors increase. The $R^{*}-Tree$ is the most successful variant of the R-Tree. In this paper, we propose a SOM-based $R^{*}-Tree$ as a new indexing method for high-dimensional feature vectors. The SOM-based $R^{*}-Tree$ combines SOM and $R^{*}-Tree$ to achieve search performance more scalable to high-dimensionalties. Self-Organizingf Maps (SOMs) provide mapping from high-dimensional feature vectors onto a two-dimensional space. The map is called a topological feature map, and preserves the mutual relationships (similarity) in the feature spaces of input data, clustering mutually similar feature vectors in neighboring nodes. Each node of the topological feature map holds a codebook vector. We experimentally compare the retrieval time cost of a SOM-based $R^{*}-Tree$ with of an SOM and $R^{*}-Tree$ using color feature vectors extracted from 40,000 images. The results show that the SOM-based $R^{*}-Tree$ outperform both the SOM and $R^{*}-Tree$ due to reduction of the number of nodes to build $R^{*}-Tree$ and retrieval time cost.

  • PDF

An Analysis of the Differences in Management Performance by Business Categories from the Perspective of Small Business Systematization (영세 소상공인 조직화에 대한 직능업종별 차이분석과 경영성과)

  • Suh, Geun-Ha;Seo, Mi-Ok;Yoon, Sung-Wook
    • Journal of Distribution Science
    • /
    • v.9 no.2
    • /
    • pp.111-122
    • /
    • 2011
  • The purpose of this study is to survey the successful cases of small and medium Business Systematization Cognition by examining their entrepreneurial characteristics and analysing the factors affecting their success. To that end, previous studies on the association types of small businesses were studied. A research model was developed, and research hypotheses for an empirical analysis were established upon it. Suh et al. (2010) insist on the importance of Small Business Systematization in Korea but also show that small business performance is suffering: they are too small to stand alone. That is why association is so crucial for them: they must stand together. Unfortunately, association is difficult, as they have few specific links and little motivation. Even in franchising networks, association tends to be initiated by big franchisers, not small ones. In that sense, association among small businesses is crucial for their long-term survival. With this in mind, this study examines how they think and feel about the issue of 'Industrial Classification', how important Industrial Classification is to their business success, and what kinds of problems it raises in the markets. This study seeks the different cognitions among the association types of small businesses from the perspectives of participation motivation, systematization expectation, policy demand level, and management performance. We assume that different industrial classification types of small businesses will have different cognitions concerning these factors. There are four basic industrial classification types of small businesses: retail sales, restaurant, service, and manufacturing. To date, most of the studies in this area have focused on collecting data on the external environments of small businesses or performing statistical analyses on their status. In this study, we surveyed 4 market areas in Busan, Masan, and Changwon in Korea, where business associations consist of merchants, shop owners, and traders. We surveyed 330 shops and merchants by sending a questionnaire or visiting. Finally, 268 questionnaires were collected and used for the analysis. An ANOVA, T-test, and regression analyses were conducted to test the research hypotheses. The results demonstrate that there are differences in cognition depending upon the industrial classification type. Restaurants generally have a higher cognition concerning job offer problems and a lower cognition concerning their competitiveness. Restaurants also depend more on systematization expectation than do the other industrial classification types. On the policy demand level, restaurants have a higher cognition. This study identifies several factors that are contributing to management performance through differences in cognition that depend upon association type: systematization expectation and policy demand level have positive effects on management performance; participation motivation has a negative effect on management performance. We confirm also that the image factors of different cognitions are linked to an awareness of the value of systematization and that these factors show sequential and continual patterns in the course of generating performances. In conclusion, this study carries significant implications in its classifying of small businesses into the four different associational types (retail sales, restaurant, services, and manufacturing). We believe our study to be the first one to conduct an empirical survey in this subject area. More studies in this area will likely use our research frameworks. The data show that regionally based industrial classification associations such as those in rural cities or less developed areas tend to suffer more problems than those in urban areas. Moreover, restaurants suffer more problems than the norm. Most of the problems raised in this study concern the act of 'associating itself'. Most associations have serious difficulties in associating. On the other hand, the area where they have the least policy demand is that of service types. This study contributes to the argument that associating, rather than financial assistance or management consulting, promotes the start-up and managerial performance of small businesses. This study also has some limitations. The main limitation is the number of questionnaires. We could not survey all the industrial classification types across the country because of budget and time limitations. If we had, we could have produced many more useful results and enhanced the precision of our analysis. The history of systemization is very short and the number of industrial classification associations is relatively low in Korea. We should keep in mind, though, that this is very crucial to systemization entrepreneurs starting their businesses, as it can heavily affect their chances of success. Being strongly associated with each other might be critical to the business success of industrial classification members. Thus, the government needs to put more effort and resources into supporting the drive of industrial classification members to become more strongly associated.

  • PDF

Analysis of Classification Characteristics for Rainfall-runoff and TOC Variation according to the Change of Map Size and Array using SOM (SOM 적용을 위한 Map Size와 Array의 변화에 따른 강우-유출 및 TOC관계 분석)

  • Park, Sung-Chun;Kim, Yong-Gu;Roh, Kyong-Bum;Lee, Han-Min
    • Proceedings of the Korea Water Resources Association Conference
    • /
    • 2008.05a
    • /
    • pp.2066-2070
    • /
    • 2008
  • 본 연구는 인공신경망(Artificial Neural Networks: ANNs)기법의 일종인 자기조직화(Self Organizing Map: SOM) 이론을 이용한다. 자기조직화 특성을 이용하여 스스로 학습이 가능하고, 구조상 수행이 빨라 학습 단계에 소요되는 시간을 줄 일 수 있는 장점을 가진 자기조직화 이론을 도입하고, 수질자료 중 전체 유기물의 양을 나타내며 난분해성 물질에 대한 해석이 가능하고 재현성이 탁월한 TOC 와 강우-유출량 자료의 분포적 양상과 특징을 분석하여 예측을 위한 모형화 과정에 기여하고자 한다. 최적의 Map Size와 Map Array 결정을 위해 수집된 강우와 유출량자료 및 TOC 자료에 대해 Garcia의 경험식을 이용하여 Map을 구성하는 단위구조의 총 수(M)를 산정하여 M값에 따른 종방향 및 횡방향 크기를 결정하는 다수의 Map 크기를 검토하고, 또한 Map 배열은 2차원 배열의 사각형배열(Rectangular array)과 육각형배열(Hexagonal array)에 대해서도 복합적으로 검토하여 최적의 특성조건을 결정하여 강우-유출 및 TOC 관계의 분할특성을 분석한다.

  • PDF

Improved Speed of Convergence in Self-Organizing Map using Dynamic Approximate Curve (동적 근사곡선을 이용한 자기조직화 지도의 수렴속도 개선)

  • Kil, Min-Wook;Kim, Gui-Joung;Lee, Geuk
    • Journal of Korea Multimedia Society
    • /
    • v.3 no.4
    • /
    • pp.416-423
    • /
    • 2000
  • The existing self-organizing feature map of Kohonen has weakpoint that need too much input patterns in order to converse into the learning rate and equilibrium state when it trains. Making up for the current weak point, B.Bavarian suggested the method of that distributed the learning rate such as Gaussian function. However, this method has also a disadvantage which can not achieve the right self-organizing. In this paper, we proposed the method of improving the convergence speed and the convergence rate of self-organizing feature map converting the Gaussian function into dynamic approximate curve used in when trains the self-organizing feature map.

  • PDF