针对数据挖掘结果集数量巨大的特点,基于Focus+Context人机交互可视化技术实现结果集的B roadV iew and D etail on D em and导航可以有效帮助对挖掘结果的聚焦与探询,进而帮助用户快速找到所需要的信息。给出了基于规则层次凝聚类与Foc...针对数据挖掘结果集数量巨大的特点,基于Focus+Context人机交互可视化技术实现结果集的B roadV iew and D etail on D em and导航可以有效帮助对挖掘结果的聚焦与探询,进而帮助用户快速找到所需要的信息。给出了基于规则层次凝聚类与Focus+Context技术的可视化系统方法与原形系统,有效地解决了巨量规则的有效浏览与可视化问题,避免了直接对规则元素图形显示效果不佳的问题,从而有利于挖掘的应用。展开更多
The international conference on mountain development in a context of global change with special focus on the Himalayas was held in Kathmandu, Nepal on April 21-26.
Globe-based Digital Earth(DE)is a promising system that uses 3D models of the Earth for integration,organization,processing,and visualization of vast multiscale geospatial datasets.The growing size and scale of geospa...Globe-based Digital Earth(DE)is a promising system that uses 3D models of the Earth for integration,organization,processing,and visualization of vast multiscale geospatial datasets.The growing size and scale of geospatial datasets present significant obstacles to interactive viewing and meaningful visualizations of these DE systems.To address these challenges,we present a novel web-based multiresolution DE system using a hierarchical discretization of the globe on both server and client sides.The presented web-based system makes use of a novel data encoding technique for rendering large multiscale geospatial datasets,with the additional capability of displaying multiple simultaneous viewpoints.Only the data needed for the current views and scales are encoded and processed.We leverage the power of GPU acceleration on the client-side to perform real-time data rendering and dynamic styling.Efficient rendering of multiple views allows us to support multilevel focus+context visualization,an effective approach to navigate through large multiscale global datasets.The client–server interaction as well as the data encoding,rendering,styling,and visualization techniques utilized by our presented system contribute toward making DE more accessible and informative.展开更多
Hierarchical abstraction is a scalable strategy to deal with large networks.Existing visualization methods have allowed to aggregate the network nodes into hierarchies based on the node attributes or network topology,...Hierarchical abstraction is a scalable strategy to deal with large networks.Existing visualization methods have allowed to aggregate the network nodes into hierarchies based on the node attributes or network topology,each of which has its own advantage.Very few previous system has the capability to enjoy the best of both worlds.This paper presents OnionGraph,an integrated framework for the exploratory visual analysis of heterogeneous multivariate networks.OnionGraph allows nodes to be aggregated based on either node attributes,topology,or a hierarchical combination of both.These aggregations can be split,merged and filtered under the focus+context interaction model,or automatically traversed by the information-theoretic navigation method.Node aggregations that contain subsets of nodes are displayed by the onion metaphor,indicating the level and details of the abstraction.We have evaluated the OnionGraph tool in three real-world cases.Performance experiments demonstrate that on a commodity desktop,our method can scale to million-node networks while preserving the interactivity for analysis.展开更多
基金SuppoSed by the National Natural Science Foundation of China under Grant Nos.6067319560703078(国家自然科学基金)+2 种基金the National High-Tech Research and Development Plan of China under Grant No.2007AA04Z113(国家高技术研究发展计划(863))the National Basic Research Program of China under Grant No.2006CB303105(国家重点基础研究发展规划(973))the National Key Technology R&D Program of China under Grant No.2006BAF01A17(国家科技支撑计划)
文摘针对数据挖掘结果集数量巨大的特点,基于Focus+Context人机交互可视化技术实现结果集的B roadV iew and D etail on D em and导航可以有效帮助对挖掘结果的聚焦与探询,进而帮助用户快速找到所需要的信息。给出了基于规则层次凝聚类与Focus+Context技术的可视化系统方法与原形系统,有效地解决了巨量规则的有效浏览与可视化问题,避免了直接对规则元素图形显示效果不佳的问题,从而有利于挖掘的应用。
文摘The international conference on mountain development in a context of global change with special focus on the Himalayas was held in Kathmandu, Nepal on April 21-26.
基金supported in part by the National Science and Engineering Research Council(NSERC)of Canadathe PYXIS innovation inc.
文摘Globe-based Digital Earth(DE)is a promising system that uses 3D models of the Earth for integration,organization,processing,and visualization of vast multiscale geospatial datasets.The growing size and scale of geospatial datasets present significant obstacles to interactive viewing and meaningful visualizations of these DE systems.To address these challenges,we present a novel web-based multiresolution DE system using a hierarchical discretization of the globe on both server and client sides.The presented web-based system makes use of a novel data encoding technique for rendering large multiscale geospatial datasets,with the additional capability of displaying multiple simultaneous viewpoints.Only the data needed for the current views and scales are encoded and processed.We leverage the power of GPU acceleration on the client-side to perform real-time data rendering and dynamic styling.Efficient rendering of multiple views allows us to support multilevel focus+context visualization,an effective approach to navigate through large multiscale global datasets.The client–server interaction as well as the data encoding,rendering,styling,and visualization techniques utilized by our presented system contribute toward making DE more accessible and informative.
文摘Hierarchical abstraction is a scalable strategy to deal with large networks.Existing visualization methods have allowed to aggregate the network nodes into hierarchies based on the node attributes or network topology,each of which has its own advantage.Very few previous system has the capability to enjoy the best of both worlds.This paper presents OnionGraph,an integrated framework for the exploratory visual analysis of heterogeneous multivariate networks.OnionGraph allows nodes to be aggregated based on either node attributes,topology,or a hierarchical combination of both.These aggregations can be split,merged and filtered under the focus+context interaction model,or automatically traversed by the information-theoretic navigation method.Node aggregations that contain subsets of nodes are displayed by the onion metaphor,indicating the level and details of the abstraction.We have evaluated the OnionGraph tool in three real-world cases.Performance experiments demonstrate that on a commodity desktop,our method can scale to million-node networks while preserving the interactivity for analysis.
