Automatic visualization generates meaningful visualizations to support data analysis and pattern finding for novice or casual users who are not familiar with visualization design.Current automatic visualization approa...Automatic visualization generates meaningful visualizations to support data analysis and pattern finding for novice or casual users who are not familiar with visualization design.Current automatic visualization approaches adopt mainly aggregation and filtering to extract patterns from the original data.However,these limited data transformations fail to capture complex patterns such as clusters and correlations.Although recent advances in feature engineering provide the potential for more kinds of automatic data transformations,the auto-generated transformations lack explainability concerning how patterns are connected with the original features.To tackle these challenges,we propose a novel explainable recommendation approach for extended kinds of data transformations in automatic visualization.We summarize the space of feasible data transformations and measures on explainability of transformation operations with a literature review and a pilot study,respectively.A recommendation algorithm is designed to compute optimal transformations,which can reveal specified types of patterns and maintain explainability.We demonstrate the effectiveness of our approach through two cases and a user study.展开更多
Automatic infographics generators employ machine learning algorithms/user-defined rules and visual embellishments into the creation of infographics.It is an emerging topic in the field of information visualization tha...Automatic infographics generators employ machine learning algorithms/user-defined rules and visual embellishments into the creation of infographics.It is an emerging topic in the field of information visualization that has requirements in many sectors,such as dashboard design,data analysis,and visualization recommendation.The growing popularity of visual analytics in recent years brings increased attention to automatic infographics.This creates the need for a broad survey that reviews and assesses the significant advances in this field.Automatic tools aim to lower the barrier for visually analyzing data by automatically generating visualizations for analysts to search and make a choice,instead of manually specifying.This survey reviews and classifies automatic tools and papers of visualization recommendations into a set of application categories including networkgraph visualizations,annotation visualizations,and storytelling visualization.More importantly,this report presents several challenges and promising directions for future work in the field of automatic infographics and visualization recommendations.展开更多
This paper presents a survey on automatic or semi-automatic recommendation systems that help users create dashboards.It starts by showing the important role that dashboards play in data science,and gives an informal d...This paper presents a survey on automatic or semi-automatic recommendation systems that help users create dashboards.It starts by showing the important role that dashboards play in data science,and gives an informal definition of dashboards,i.e.,a set of visualizations possibly with linkage,a screen layout and user feedback.We are mainly interested in systems that use a fully or partially automatic mechanism to recommend dashboards to users.This automation includes the suggestion of data and visualizations,the optimization of the layout and the use of user feedback.We position our work with respect to existing surveys.Starting from a set of over 1000 papers,we have selected and analyzed 19 papers/systems along several dimensions.The main dimensions were the set of considered visualizations,the suggestion method,the utility/objective functions,the layout,and the user interface.We conclude by highlighting the main achievements in this domain and by proposing perspectives.展开更多
Pulse diagnosis equipment used in Traditional Chinese Medicine(TCM)has long been developed for collecting pulse information and in TCM research.However,it is still difficult to implement pulse taking automatically or ...Pulse diagnosis equipment used in Traditional Chinese Medicine(TCM)has long been developed for collecting pulse information and in TCM research.However,it is still difficult to implement pulse taking automatically or efficiently in clinical practice.Here,we present a digital protocol for TCM pulse information collection based on bionic pulse diagnosis equipment,which ensures high efficiency,reliability and data integrity of pulse diagnosis information.A four-degree-of-freedom pulse taking platform together with a wrist bracket can satisfy the spatial positioning and angle requirements for individually adaptive pulse acquisition.Three-dimensional reconstruction of a wrist surface and an image localization model are combined to provide coordinates of the acquisition position and detection direction automatically.Three series elastic joints can not only simulate the TCM pulse taking method that“Three fingers in a straight line,the middle finger determining the‘Guan’location and finger pulp pressing on the radial artery,”but also simultaneously carry out the force-controlled multi-gradient pressing process.In terms of pulse information integrity,this proposed protocol can generate rich pulse information,including basic individual information,pulse localization distribution,multi-gradient dynamic pulse force time series,and objective pulse parameters,which can help establish the fundamental data sets that are required as the pulse phenotype for subsequent comprehensive analysis of pulse diagnosis.The implementation of this scheme is beneficial to promote the standardization of the digitalized collection of pulse information,the effectiveness of detecting abnormal health status,and the promotion of the fundamental and clinical research of TCM,such as TCM pulse phenomics.展开更多
基金Project supported by the National Natural Science Foundation of China(No.62132017)the Fundamental Research Funds for the Central Universities,China(No.226202200235)。
文摘Automatic visualization generates meaningful visualizations to support data analysis and pattern finding for novice or casual users who are not familiar with visualization design.Current automatic visualization approaches adopt mainly aggregation and filtering to extract patterns from the original data.However,these limited data transformations fail to capture complex patterns such as clusters and correlations.Although recent advances in feature engineering provide the potential for more kinds of automatic data transformations,the auto-generated transformations lack explainability concerning how patterns are connected with the original features.To tackle these challenges,we propose a novel explainable recommendation approach for extended kinds of data transformations in automatic visualization.We summarize the space of feasible data transformations and measures on explainability of transformation operations with a literature review and a pilot study,respectively.A recommendation algorithm is designed to compute optimal transformations,which can reveal specified types of patterns and maintain explainability.We demonstrate the effectiveness of our approach through two cases and a user study.
基金National Natural Science Foundation of China(No.61972356,61902350)Zhejiang Provincial Natural Science Foundation of China(NO.LY19F020026)+1 种基金Zhejiang Provincial Key Research and Development Program of China(No.2019C01009)Fundamental Research Funds for the Provincial Universities of Zhejiang(NO.RF-C2019001).
文摘Automatic infographics generators employ machine learning algorithms/user-defined rules and visual embellishments into the creation of infographics.It is an emerging topic in the field of information visualization that has requirements in many sectors,such as dashboard design,data analysis,and visualization recommendation.The growing popularity of visual analytics in recent years brings increased attention to automatic infographics.This creates the need for a broad survey that reviews and assesses the significant advances in this field.Automatic tools aim to lower the barrier for visually analyzing data by automatically generating visualizations for analysts to search and make a choice,instead of manually specifying.This survey reviews and classifies automatic tools and papers of visualization recommendations into a set of application categories including networkgraph visualizations,annotation visualizations,and storytelling visualization.More importantly,this report presents several challenges and promising directions for future work in the field of automatic infographics and visualization recommendations.
文摘This paper presents a survey on automatic or semi-automatic recommendation systems that help users create dashboards.It starts by showing the important role that dashboards play in data science,and gives an informal definition of dashboards,i.e.,a set of visualizations possibly with linkage,a screen layout and user feedback.We are mainly interested in systems that use a fully or partially automatic mechanism to recommend dashboards to users.This automation includes the suggestion of data and visualizations,the optimization of the layout and the use of user feedback.We position our work with respect to existing surveys.Starting from a set of over 1000 papers,we have selected and analyzed 19 papers/systems along several dimensions.The main dimensions were the set of considered visualizations,the suggestion method,the utility/objective functions,the layout,and the user interface.We conclude by highlighting the main achievements in this domain and by proposing perspectives.
基金supported by the Shanghai 2021 Science and Technology Innovation Action Plan Project(Grant No.21S31902500)the Independent Deployment of Scientific Research Projects of Jihua Laboratory(Grant No.X190051TB190)the National Natural Science Foundation of China(Grant No.U1913216).
文摘Pulse diagnosis equipment used in Traditional Chinese Medicine(TCM)has long been developed for collecting pulse information and in TCM research.However,it is still difficult to implement pulse taking automatically or efficiently in clinical practice.Here,we present a digital protocol for TCM pulse information collection based on bionic pulse diagnosis equipment,which ensures high efficiency,reliability and data integrity of pulse diagnosis information.A four-degree-of-freedom pulse taking platform together with a wrist bracket can satisfy the spatial positioning and angle requirements for individually adaptive pulse acquisition.Three-dimensional reconstruction of a wrist surface and an image localization model are combined to provide coordinates of the acquisition position and detection direction automatically.Three series elastic joints can not only simulate the TCM pulse taking method that“Three fingers in a straight line,the middle finger determining the‘Guan’location and finger pulp pressing on the radial artery,”but also simultaneously carry out the force-controlled multi-gradient pressing process.In terms of pulse information integrity,this proposed protocol can generate rich pulse information,including basic individual information,pulse localization distribution,multi-gradient dynamic pulse force time series,and objective pulse parameters,which can help establish the fundamental data sets that are required as the pulse phenotype for subsequent comprehensive analysis of pulse diagnosis.The implementation of this scheme is beneficial to promote the standardization of the digitalized collection of pulse information,the effectiveness of detecting abnormal health status,and the promotion of the fundamental and clinical research of TCM,such as TCM pulse phenomics.
