• Title/Summary/Keyword: 속성분류

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Landscape Object Classification and Attribute Information System for Standardizing Landscape BIM Library (조경 BIM 라이브러리 표준화를 위한 조경객체 및 속성정보 분류체계)

  • Kim, Bok-Young
    • Journal of the Korean Institute of Landscape Architecture
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    • v.51 no.2
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    • pp.103-119
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    • 2023
  • Since the Korean government has decided to apply the policy of BIM (Building Information Modeling) to the entire construction industry, it has experienced a positive trend in adoption and utilization. BIM can reduce workloads by building model objects into libraries that conform to standards and enable consistent quality, data integrity, and compatibility. In the domestic architecture, civil engineering, and the overseas landscape architecture sectors, many BIM library standardization studies have been conducted, and guidelines have been established based on them. Currently, basic research and attempts to introduce BIM are being made in Korean landscape architecture field, but the diffusion has been delayed due to difficulties in application. This can be addressed by enhancing the efficiency of BIM work using standardized libraries. Therefore, this study aims to provide a starting point for discussions and present a classification system for objects and attribute information that can be referred to when creating landscape libraries in practice. The standardization of landscape BIM library was explored from two directions: object classification and attribute information items. First, the Korean construction information classification system, product inventory classification system, landscape design and construction standards, and BIM object classification of the NLA (Norwegian Association of Landscape Architects) were referred to classify landscape objects. As a result, the objects were divided into 12 subcategories, including 'trees', 'shrubs', 'ground cover and others', 'outdoor installation', 'outdoor lighting facility', 'stairs and ramp', 'outdoor wall', 'outdoor structure', 'pavement', 'curb', 'irrigation', and 'drainage' under five major categories: 'landscape plant', 'landscape facility', 'landscape structure', 'landscape pavement', and 'irrigation and drainage'. Next, the attribute information for the objects was extracted and structured. To do this, the common attribute information items of the KBIMS (Korean BIM Standard) were included, and the object attribute information items that vary according to the type of objects were included by referring to the PDT (Product Data Template) of the LI (UK Landscape Institute). As a result, the common attributes included information on 'identification', 'distribution', 'classification', and 'manufacture and supply' information, while the object attributes included information on 'naming', 'specifications', 'installation or construction', 'performance', 'sustainability', and 'operations and maintenance'. The significance of this study lies in establishing the foundation for the introduction of landscape BIM through the standardization of library objects, which will enhance the efficiency of modeling tasks and improve the data consistency of BIM models across various disciplines in the construction industry.

Temporal Associative Classification based on Calendar Patterns (캘린더 패턴 기반의 시간 연관적 분류 기법)

  • Lee Heon Gyu;Noh Gi Young;Seo Sungbo;Ryu Keun Ho
    • Journal of KIISE:Databases
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    • v.32 no.6
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    • pp.567-584
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    • 2005
  • Temporal data mining, the incorporation of temporal semantics to existing data mining techniques, refers to a set of techniques for discovering implicit and useful temporal knowledge from temporal data. Association rules and classification are applied to various applications which are the typical data mining problems. However, these approaches do not consider temporal attribute and have been pursued for discovering knowledge from static data although a large proportion of data contains temporal dimension. Also, data mining researches from temporal data treat problems for discovering knowledge from data stamped with time point and adding time constraint. Therefore, these do not consider temporal semantics and temporal relationships containing data. This paper suggests that temporal associative classification technique based on temporal class association rules. This temporal classification applies rules discovered by temporal class association rules which extends existing associative classification by containing temporal dimension for generating temporal classification rules. Therefore, this technique can discover more useful knowledge in compared with typical classification techniques.

Preference Analysis for Location Based Constructs on Smartphone Environment (스마트폰 환경에서 위치기반 속성에 대한 선호도 분석)

  • Nam, Soo-tai;Kim, Do-Goan;Jin, Chan-yong
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2014.05a
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    • pp.171-174
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    • 2014
  • Increasingly important user based service on the smart media era, and increasing awareness about the user experience. In this study, by considering these realities, what impact location based constructs on smartphone environment, continuous intention to use you want to identification. Thus, this study conducted of preference the influencing factors for location based constructs. First steps, based constructs known empirical studies were categorized information, entertainment, safe&emergency, navigation&tracking and advertising& commerce. Second Steps, the categorized factors were analyzed preference relationship between constructs using AHP(analytic hierarchy process) technique. Questionnaire survey was conducted to those who employees S Telecom in Busan city and Gyeongnam province during 2000. 4. 15 and 2014. 4. 30. The result of the analysis might be summarized that the navigation(0.133) has the highest preference ran in the constructs. Based on these findings, several theoretical and practical implications were suggested and discussed.

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Performance Analysis of Opinion Mining using Word2vec (Word2vec을 이용한 오피니언 마이닝 성과분석 연구)

  • Eo, Kyun Sun;Lee, Kun Chang
    • Proceedings of the Korea Contents Association Conference
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    • 2018.05a
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    • pp.7-8
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    • 2018
  • This study proposes an analysis of the Word2vec-based machine learning classifiers for the sake of opinion mining tasks. As a bench-marking method, BOW (Bag-of-Words) was adopted. On the basis of utilizing the Word2vec and BOW as feature extraction methods, we applied Laptop and Restaurant dataset to LR, DT, SVM, RF classifiers. The results showed that the Word2vec feature extraction yields more improved performance.

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Plant equipment data system development based of ISO 15926 (ISO 15926 국제표준을 이용한 플랜트 기자재 정보 시스템 구축)

  • Ahn, Ho-Jun;Park, Ho-Byung;Choe, Jee-Woong
    • Proceedings of the Korea Information Processing Society Conference
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    • 2007.05a
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    • pp.477-480
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    • 2007
  • 국제표준규격인 ISO 10303(STEP), ISO 13584(PLIB), ISO 15926을 연구하고 해외건설 플랜트의 기자재 데이터를 입수하여 전문가를 통한 분석, 분류 및 국제표준규격(ISO 15926 RDL) 기반과 비교하여 분류체계 구축 및 속성정보 정의 작업을 수행하였다. 통합 및 분리가 필요한 기자재 클래스에 대해서는 통합, 분리 작업을 수행하였고 적용 가능한 속성정보가 있을 경우는 클래스별로 확장 적용하였다. 이에, 5단계 레벨, 637개의 분류체계가 구성되었고 개방형 구조의 XML으로 플랜트 기자재 정보를 구축하여 계층구조 분류트리 표현 및 해당 기자재의 제품에 대한 상세 정보를 나타내었다. 또한, 제품정보를 통합검색, 카테고리검색, 상세검색, 논리검색 기능으로 검색, 확인할 수 있고 표준 및 제품, 업체, 시스템을 관리하는 기자재 정보 관리 시스템을 구현하였다.

Prompt Tuning For Korean Aspect-Based Sentiment Analysis (프롬프트 튜닝기법을 적용한 한국어 속성기반 감정분석)

  • Bong-Su Kim;Hyun-Kyu Jeon;Seung-Ho Choi;Ji-Yoon Kim;Jung-Hoon Jang
    • Annual Conference on Human and Language Technology
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    • 2023.10a
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    • pp.50-55
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    • 2023
  • 속성 기반 감정 분석은 텍스트 내에서 감정과 해당 감정이 특정 속성, 예를 들어 제품의 특성이나 서비스의 특징에 어떻게 연결되는지를 분석하는 태스크이다. 본 논문에서는 속성 기반 감정 분석 데이터를 사용한 다중 작업-토큰 레이블링 문제에 프롬프트 튜닝 기법을 적용하기 위한 포괄적인 방법론을 소개한다. 이러한 방법론에는 토큰 레이블링 문제를 시퀀스 레이블링 문제로 일반화하기 위한 감정 표현 영역 검출 파이프라인이 포함된다. 또한 분리된 시퀀스들을 속성과 감정에 대해 분류 하기 위한 템플릿을 선정하고, 데이터셋 특성에 맞는 레이블 워드를 확장하는 방법을 제안함으써 모델의 성능을 최적화한다. 최종적으로, 퓨샷 세팅에서의 속성 기반 감정 분석 태스크에 대한 몇 가지 실험 결과와 분석을 제공한다. 구축된 데이터와 베이스라인 모델은 AIHUB(www.aihub.or.kr)에 공개되어 있다.

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A Study on the Service Quality Evaluation in Electronic Customs Clearance Making Use of Kano-IGA Integrated Approach (Kano-IGA 통합접근법을 이용한 전자통관 서비스 품질의 평가에 관한 연구)

  • Song, Sun-Yok
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.20 no.10
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    • pp.54-61
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    • 2019
  • This paper reports a comparative review of the service quality attributes of Electronic Customs Clearance (UNI-PASS) by applying the Kano model, Timko's BW coefficients, and IGA model, as reported by Tontini et al. in terms of a service quality evaluation of electronic customs clearance as the comprehensive national customs administration information system. In addition, this study examined which quality attributes should be focused on to improve the service quality and enhance customer satisfaction using the electronic customs clearance service. The Kano, Timko, and IGA models were classified into the four common quality attributes: attractive quality, one-dimensional quality, must-be quality, and indifferent quality. Because the integrated approach was used, one-dimensional quality was included in the area for critical improvement, while the must-be quality was included in the area for intensive maintenance. In addition, the indifferent quality was included in the area of carefree, while the attractive quality was included in the area of competitive advantage.

Block Classification of Document Images by Block Attributes and Texture Features (블록의 속성과 질감특징을 이용한 문서영상의 블록분류)

  • Jang, Young-Nae;Kim, Joong-Soo;Lee, Cheol-Hee
    • Journal of Korea Multimedia Society
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    • v.10 no.7
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    • pp.856-868
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    • 2007
  • We propose an effective method for block classification in a document image. The gray level document image is converted to the binary image for a block segmentation. This binary image would be smoothed to find the locations and sizes of each block. And especially during this smoothing, the inner block heights of each block are obtained. The gray level image is divided to several blocks by these location informations. The SGLDM(spatial gray level dependence matrices) are made using the each gray-level document block and the seven second-order statistical texture features are extracted from the (0,1) direction's SGLDM which include the document attributes. Document image blocks are classified to two groups, text and non-text group, by the inner block height of the block at the nearest neighbor rule. The seven texture features(that were extracted from the SGLDM) are used for the five detail categories of small font, large font, table, graphic and photo blocks. These document blocks are available not only for structure analysis of document recognition but also the various applied area.

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A Study on the Analysis of the Morphological Attributes for the Design Development of LED Lighting Fixtures (LED조명등기구 디자인 개발을 위한 형태적 속성 분석에 관한 연구)

  • Yun, Bong Shik;Cho, Kwang Su
    • Smart Media Journal
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    • v.5 no.4
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    • pp.103-110
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    • 2016
  • This study aims to establish the standards to give the design weight in case when developing equipment designs, by classifying products with similar purposes in accordance with the morphological characteristics and also extracting the typicality. Limiting the sampling group for the extraction of the typicality to a pendant-type and a ceiling buried-type through the preceding case study and consultation with experts, the survey was conducted for majors and relevant workers in six cities, sampling products released in Korea and Japan before May 2016. The 1st survey was about the Morphological classification, and the 2nd times about the extraction of the typicality while the 3rd one was about the classification of the morphological attributes. By drawing the design attributes based on the functional/morphological classification and formative principles, it aimed to establish the base of the future research on the measurement of design weight. The results of this study aim to efficiently establish the roles of design technology in accordance with changes in the lighting fixture market caused by the substitution of light sources, and also to draw the development direction to rapidly cope with the accelerated changes in lighting design types and corporate R&D.

Generation and Selection of Nominal Virtual Examples for Improving the Classifier Performance (분류기 성능 향상을 위한 범주 속성 가상예제의 생성과 선별)

  • Lee, Yu-Jung;Kang, Byoung-Ho;Kang, Jae-Ho;Ryu, Kwang-Ryel
    • Journal of KIISE:Software and Applications
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    • v.33 no.12
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    • pp.1052-1061
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    • 2006
  • This paper presents a method of using virtual examples to improve the classification accuracy for data with nominal attributes. Most of the previous researches on virtual examples focused on data with numeric attributes, and they used domain-specific knowledge to generate useful virtual examples for a particularly targeted learning algorithm. Instead of using domain-specific knowledge, our method samples virtual examples from a naive Bayesian network constructed from the given training set. A sampled example is considered useful if it contributes to the increment of the network's conditional likelihood when added to the training set. A set of useful virtual examples can be collected by repeating this process of sampling followed by evaluation. Experiments have shown that the virtual examples collected this way.can help various learning algorithms to derive classifiers of improved accuracy.