• Title/Summary/Keyword: Visual Mining

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KNN-based Image Annotation by Collectively Mining Visual and Semantic Similarities

  • Ji, Qian;Zhang, Liyan;Li, Zechao
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.9
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    • pp.4476-4490
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    • 2017
  • The aim of image annotation is to determine labels that can accurately describe the semantic information of images. Many approaches have been proposed to automate the image annotation task while achieving good performance. However, in most cases, the semantic similarities of images are ignored. Towards this end, we propose a novel Visual-Semantic Nearest Neighbor (VS-KNN) method by collectively exploring visual and semantic similarities for image annotation. First, for each label, visual nearest neighbors of a given test image are constructed from training images associated with this label. Second, each neighboring subset is determined by mining the semantic similarity and the visual similarity. Finally, the relevance between the images and labels is determined based on maximum a posteriori estimation. Extensive experiments were conducted using three widely used image datasets. The experimental results show the effectiveness of the proposed method in comparison with state-of-the-arts methods.

Multi-Objective Design Exploration and its Applications

  • Obayashi, Shigeru;Jeong, Shin-Kyu;Shimoyama, Koji;Chiba, Kazuhisa;Morino, Hiroyuki
    • International Journal of Aeronautical and Space Sciences
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    • v.11 no.4
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    • pp.247-265
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    • 2010
  • Multi-objective design exploration (MODE) and its applications are reviewed as an attempt to utilize numerical simulation in aerospace engineering design. MODE reveals the structure of the design space based on trade-off information. A self-organizing map (SOM) is incorporated into MODE as a visual data mining tool for the design space. SOM divides the design space into clusters with specific design features. This article reviews existing visual data mining techniques applied to engineering problems. Then, we discuss three applications of MODE: multidisciplinary design optimization for a regional-jet wing, silent supersonic technology demonstrator and centrifugal diffusers.

An Activity Analysis Method for Workflow Visual Verification and Mining (워크플로우 가시적 검증 및 마이닝을 위한 액티비티 분석 방법)

  • Kim, Kwang-Hoon
    • Journal of Internet Computing and Services
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    • v.9 no.4
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    • pp.133-142
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    • 2008
  • This paper conceives and implements an activity analysis method as a tool to be used for workflow visual verification and mining. One of the recent issues in the workflow and business process literature is to refine and to improve the deployed workflows and business processes. The activity analysis method proposed in this paper provides a way to fine a set of activities being directly affected by the specific activity that a user tries to change its properties. I would strongly believe that the method can be a useful solution for the dynamic changes and visual verifications problems of workflow models as well as the workflow process mining problems. Finally, to prove the possibility of the proposed method and its applicability, we apply to a workflow model of the electronic approval system run by a real corporation.

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Introduction to Visual Analytics Research (비주얼 애널리틱스 연구 소개)

  • Oh, Yousang;Lee, Chunggi;Oh, Juyoung;Yang, Jihyeon;Kwag, Heena;Moon, Seongwoo;Park, Sohwan;Ko, Sungahn
    • Journal of the Korea Computer Graphics Society
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    • v.22 no.5
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    • pp.27-36
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    • 2016
  • As big data become more complex than ever, there has been a need for various techniques and approaches to better analyze and explore such big data. A research discipline of visual analytics has been proposed to help users' visual data analysis and decision-making. Since 2006 when the first symposium of visual analytics was held, the visual analytics research has become popular as the advanced technology in computer graphics, data mining, and human-computer interaction has been incorporated in visual analytics. In this work we introduce the visual analytics research by reviewing and surveying the papers published in IEEE VAST 2015 in terms of data and visualization techniques to help domestics researchers' understanding on visual analytics.

Quick Decision Making Using Visual Dynamic Mining Tool;Spotfire (비쥬얼 다이나믹 마이닝 툴을 이용한 신속한 의사결정;Spotfire)

  • Kim, Seong-Ki
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2008.04a
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    • pp.89-91
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    • 2008
  • 엄청나게 쏟아져 나오는 데이터 홍수 속에서 오늘날의 업체와 연구기관에서는 신속하게 의사 결정을 해야 한다. 당면한 문제점들을 해결하기 위하여 접근할 수 있는 수많은 다양한 데이터 속에서 정확하게 경향을 파악하고 그 근본 원인을 찾아내어 신속하고 action을 행하는 것은 어떠한 회사에서도 성공에 있어서 가장 중요한 인자들 중의 하나이다. 초기 아이디어 도출, 연구 개발에서부터 제품의 생산, 판매 및 서비스에 이르기까지 모든 팀원들은 아주 빠르게 고도의 정확성으로 중요한 결정을 할 필요가 있다. 오늘날의 경쟁 시장에서 기업의 성공은 다른 경쟁자들보다 더 빠르게 결정을 할 수 있는 능력에 달려 있다. 이에 Sporfire에서는 사용자가 쉽고 빠르게 데이터를 분석하여 의사 결정을 할 수 있도록 다양한 기능을 제공하고 있다. 사용자가 SQL같은 전문 언어를 사용하지 않고도 다양한 데이터 source에서 쉽게 데이터를 가져오도록 Information Library를 이용할 수 있으며, 데이터베이스에 들어 있는 숫자들의 집합체를 다양한 차트와 도표들을 이용, 그래픽 적으로 제공해 줌으로써 데이터에 대하여 직관적으로 파악하여 신속하게 대응할 수 있도록 도와준다. 또한 그 결과물들을 MS 파워포인트, 엑셀시트, xml 등으로 저장하여 다른 용도로 사용할 수 있도록 하고 있다.

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Underground Mine Design and Stability Analysis at a Limestone Mine (석회석광산의 갱내채광설계 및 안정성평가)

  • Koo, Chung-Mo;Jeon, Seok-Won;Lee, In-Woo
    • Tunnel and Underground Space
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    • v.18 no.4
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    • pp.243-251
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    • 2008
  • Recently, the mining methods are changing from surface mining to underground mining because of the increment of the environmental issues and legal regulations. Therefore, the stability of underground openings is a major concern for the safety and productivity of mining operations. In this paper, a survey of structural geology and discontinuities were carried out at a limestone mine. The relevant mechanical properties of rocks were determined by the laboratory tests and rock mass classifications (RMR and Q-system) for the mine design and input data for the stability analysis. The dimensions of unsupported span for underground openings and pillar were decided based on the RMR values of rock mass classifications. The stability analysis for the suggested mine design was examined through the empirical methods (stability graph method and critical span curve) and 3-D numerical analysis (Visual-FEA).

Exploring Simultaneous Presentation in Online Restaurant Reviews: An Analysis of Textual and Visual Content

  • Lin Li;Gang Ren;Taeho Hong;Sung-Byung Yang
    • Asia pacific journal of information systems
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    • v.29 no.2
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    • pp.181-202
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    • 2019
  • The purpose of this study is to explore the effect of different types of simultaneous presentation (i.e., reviewer information, textual and visual content, and similarity between textual-visual contents) on review usefulness and review enjoyment in online restaurant reviews (ORRs), as they are interrelated yet have rarely been examined together in previous research. By using Latent Dirichlet Allocation (LDA) topic modeling and state-of-the-art machine learning (ML) methodologies, we found that review readability in textual content and salient objects in images in visual content have a significant impact on both review usefulness and review enjoyment. Moreover, similarity between textual-visual contents was found to be a major factor in determining review usefulness but not review enjoyment. As for reviewer information, reputation, expertise, and location of residence, these were found to be significantly related to review enjoyment. This study contributes to the body of knowledge on ORRs and provides valuable implications for general users and managers in the hospitality and tourism industries.

A Study on System Applications of e-CRM to Enforcement of consumer Service (e-Commerce 쇼핑몰의 소비자 서비스 강화를 위한 활용연구)

  • Kim Yeonjeong
    • Journal of the Korean Home Economics Association
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    • v.43 no.3 s.205
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    • pp.1-10
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    • 2005
  • The purpose of this study was to investigate the enforcement strategy for Consumer Service marketing of an e-Commerce shopping mall. An e-CRM for a Cosmetic e-Commerce shopping mall, Data Warehousing(DW) component, analysis of data mining of the DW, and web applications and strategies had to developed for marketing of consumer service satisfaction. The major findings were as follows: An RFM analysis was used for consumer classification, which is a fundamental process of e-CRM application. The components of the DW were web sales data and consumer data fields. The visual process of consumer segmentations (superior consumer class) for e-CRM solutions is presented. The association analysis algorithm of data mining to up-selling and cross-selling indicates an association rule. These e-CRM results apply web DB marketing and operating principles to a shopping mall. Therefore, the system applications of e-CRM to Consumer services indicate a marketing strategy for consumer-oriented management.

Analysis of Healthcare Quality Indicator using Data Mining and Decision Support System

  • Young M.Chae;Kim, Hye S.;Seung H. Ho
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2001.01a
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    • pp.352-357
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    • 2001
  • This study presents an analysis of healthcare quality indicators using data mining for developing quality improvement strategies. Specifically, important factors influencing the inpatient mortality were identified using a decision tree method for data mining based on 8,405 patients who were discharged from the study hospital during the period of December 1, 2000 and January 31, 2001. Important factors for the inpatient mortality were length of stay, disease classes, discharge departments, and age groups. The optimum range of target group in inpatient healthcare quality indicators were identified from the gains chart. In addition, a decision support system was developed to analyze and monitor trends of quality indicators using Visual Basic 6.0. Guidelines and tutorial for quality improvement activities were also included in the system. In the future, other quality indicators should be analyze to effectively support a hospital-wide continuous quality improvement (CQI) activity and the decision support system should be well integrated with the hospital OCS (Order Communication System) to support concurrent review.

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Evaluating the Characteristics of Subversive Basic Fashion Utilizing Text Mining Techniques (텍스트 마이닝(text mining) 기법을 활용한 서브버시브 베이식(subversive basics) 패션의 특성)

  • Minjung Im
    • Journal of Fashion Business
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    • v.27 no.5
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    • pp.78-92
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    • 2023
  • Fashion trends are actively disseminated through social media, which influences both their propagation and consumption. This study explored how users perceive subversive basic fashion in social media videos, by examining the associated concepts and characteristics. In addition, the factors contributing to the style's social media dissemination were identified and its distinctive features were analyzed. Through text mining analysis, 80 keywords were selected for semantic network and CONCOR analysis. TF-IDF and N-gram results indicate that subversive basic fashion involves transformative design techniques such as cutting or layering garments, emphasizing the body with thin fabrics, and creating bold visual effects. Topic modeling suggests that this fashion forms a subculture that resists mainstream norms, seeking individuality by creatively transforming the existing garments. CONCOR analysis categorized the style into six groups: forward-thinking unconventional fashion, bold and unique style, creative reworking, item utilization and combination, pursuit of easy and convenient fashion, and contemporary sensibility. Consumer actions, linked to social media, were shown to involve easily transforming and pursuing personalized styles. Furthermore, creating new styles through the existing clothing is seen as an economic and creative activity that fosters network formation and interaction. This study is significant as it addresses language expression limitations and subjectivity issues in fashion image analysis, revealing factors contributing to content reproduction through user-perceived design concepts and social media-conveyed fashion characteristics.