RISeer: Inspecting the Status and Dynamics of Regional Industrial Structure Via Visual Analytics

Ouyang, Yuanxin; Zhang, Haipeng; Hong, Suting; Li, Quan

doi:10.1109/tvcg.2022.3209351

Cited by 4 publications

(4 citation statements)

References 59 publications

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“…Arleo et al [3] visualized the variability of indicators and the spatiotemporal evolution of the relationships between objects. Similarly, Chen et al [1] proposed an interactive visualization system with new visual features to analyze the evolution process of the regional industry structure. Both these studies provided insights into financial networks from the perspective of geographical distribution.…”

Section: Visual Analysis Of Financial Networkmentioning

confidence: 99%

“…Additionally, visualization researchers have designed visual analysis tools specifically for analyzing regional industry entities. For example, to analyze individual regional industries, Chen et al [ 1 ] introduced RISeer, which combines the visual representations of bubble-like graphs and connecting lines to help users visually analyze the evolutionary dynamics of the structure of a RIN. To analyze the industrial connections within a region, Hermes conducted a visual analysis of the cash flow network, revealing the economic connections between productive sectors and geographic regions [ 2 ].…”

Section: Introductionmentioning

confidence: 99%

“…They utilized geovisualization methods to present financial networks on maps, enhancing researchers’ understanding of the geographic attributes of the nodes as well as the distribution of relationships in the financial network. In particular, RISeer, proposed by Chen et al [ 1 ], is one of the few visual analysis works designed for regional industries. It revealed the current state of the regional industry structures and their dynamic changes over time from a microscopic perspective.…”

Section: Introductionmentioning

confidence: 99%

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V4RIN: visual analysis of regional industry network with domain knowledge

Xiong,

Yu,

Shi

et al. 2024

Vis. Comput. Ind. Biomed. Art

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The regional industry network (RIN) is a type of financial network derived from industry networks that possess the capability to describe the connections between specific industries within a particular region. For most investors and financial analysts lacking extensive experience, the decision-support information provided by industry networks may be too vague. Conversely, RINs express more detailed and specific industry connections both within and outside the region. As RIN analysis is domain-specific and current financial network analysis tools are designed for generalized analytical tasks and cannot be directly applied to RINs, new visual analysis approaches are needed to enhance information exploration efficiency. In this study, we collaborated with domain experts and proposed V4RIN, an interactive visualization analysis system that integrates predefined domain knowledge and data processing methods to support users in uploading custom data. Through multiple views in the system panel, users can comprehensively explore the structure, geographical distribution, and spatiotemporal variations of the RIN. Two case studies were conducted and a set of expert interviews with five domain experts to validate the usability and reliability of our system.

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Section: Visual Analysis Of Financial Networkmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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V4RIN: visual analysis of regional industry network with domain knowledge

Xiong,

Yu,

Shi

et al. 2024

Vis. Comput. Ind. Biomed. Art

View full text Add to dashboard Cite

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“…In the PromotionLens platform [39], Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Multilayer Perception (MLP) win the comparison for providing a visual exploration of strategies for promoting e-commerce commodities. In this vein, RISeer [48] visually conducts inter-regional inspections and comparisons for urban economic development using RF and XGBoost, while LEGION [37] enables users to compare and choose regression models that were created either by feature engineering or by fine-tuning their hyperparameters.…”

Section: Ai4vis-aided Decision-makingmentioning

confidence: 99%

ClinicLens: Visual Analytics for Exploring and Optimizing the Testing Capacity of Clinics given Uncertainty

Yu¹,

Liu²,

Cao³

et al. 2023

Preprint

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Clinic testing plays a critical role in containing infectious diseases such as COVID-19. However, one of the key research questions in fighting such pandemics is how to optimize testing capacities across clinics. In particular, domain experts expect to know exactly how to adjust the features that may affect testing capacities, given that dynamics and uncertainty make this a highly challenging problem. Hence, as a tool to support both policymakers and clinicians, we collaborated with domain experts to build ClinicLens, an interactive visual analytics system for exploring and optimizing the testing capacities of clinics. ClinicLens houses a range of features based on an aggregated set of COVID-19 data. It comprises Back-end Engine and Front-end Visualization that take users through an iterative exploration chain of extracting, training, and predicting testing-sensitive features and visual representations. It also combines AI4VIS and visual analytics to demonstrate how a clinic might optimize its testing capacity given the impacts of a range of features. Three qualitative case studies along with feedback from subject-matter experts validate that ClinicLens is both a useful and effective tool for exploring the trends in COVID-19 and optimizing clinic testing capacities across regions. The entire approach has been open-sourced online: https://github.com/YuDong5018/clinic-lens.

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Design and Implementation of Interactive Learning System for Art Teaching

Fang

2023

2023 International Conference on Ambient Intelligence, Knowledge Informatics and Industrial Electronics (AIKIIE)

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RISeer: Inspecting the Status and Dynamics of Regional Industrial Structure Via Visual Analytics

Cited by 4 publications

References 59 publications

V4RIN: visual analysis of regional industry network with domain knowledge

V4RIN: visual analysis of regional industry network with domain knowledge

ClinicLens: Visual Analytics for Exploring and Optimizing the Testing Capacity of Clinics given Uncertainty

Design and Implementation of Interactive Learning System for Art Teaching

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