Data quality management,especially data cleansing,has been extensively studied for many years in the areas of data management and visual analytics.In the paper,we first review and explore the relevant work from the re...Data quality management,especially data cleansing,has been extensively studied for many years in the areas of data management and visual analytics.In the paper,we first review and explore the relevant work from the research areas of data management,visual analytics and human-computer interaction.Then for different types of data such as multimedia data,textual data,trajectory data,and graph data,we summarize the common methods for improving data quality by leveraging data cleansing techniques at different analysis stages.Based on a thorough analysis,we propose a general visual analytics framework for interactively cleansing data.Finally,the challenges and opportunities are analyzed and discussed in the context of data and humans.展开更多
An evacuation plan helps people move away from an area or a building. To assist rapid evacuation,we present an algorithm to compute the optimal route for each local region. The idea is to reduce congestion and maximiz...An evacuation plan helps people move away from an area or a building. To assist rapid evacuation,we present an algorithm to compute the optimal route for each local region. The idea is to reduce congestion and maximize the number of evacuees arriving at exits in each time span. Our system considers crowd distribution, exit locations, and corridor widths when determining optimal routes. It also simulates crowd movements during route optimization. As a basis,we expect that neighboring crowds who take different evacuation routes should arrive at respective exits at nearly the same time. If this is not the case, our system updates the routes of the slower crowds. As crowd simulation is non-linear, the optimal route is computed in an iterative manner. The system repeats until an optimal state is achieved. In addition to directly computing optimal routes for a situation, our system allows the structure of the situation to be decomposed,and determines the routes in a hierarchical manner.This strategy not only reduces the computational cost but also enables crowds in different regions to evacuate with different priorities. Experimental results,with visualizations, demonstrate the feasibility of our evacuation route optimization method.展开更多
基金This research was funded by National Key R&D Program of China(No.SQ2018YFB100002)the National Natural Science Foundation of China(No.s 61761136020,61672308)+5 种基金Microsoft Research Asia,Fraunhofer Cluster of Excellence on"Cognitive Internet Technologies",EU through project Track&Know(grant agreement 780754)NSFC(61761136020)NSFC-Zhejiang Joint Fund for the Integration of Industrialization and Informatization(U1609217)Zhejiang Provincial Natural Science Foundation(LR18F020001)NSFC Grants 61602306Fundamental Research Funds for the Central Universities。
文摘Data quality management,especially data cleansing,has been extensively studied for many years in the areas of data management and visual analytics.In the paper,we first review and explore the relevant work from the research areas of data management,visual analytics and human-computer interaction.Then for different types of data such as multimedia data,textual data,trajectory data,and graph data,we summarize the common methods for improving data quality by leveraging data cleansing techniques at different analysis stages.Based on a thorough analysis,we propose a general visual analytics framework for interactively cleansing data.Finally,the challenges and opportunities are analyzed and discussed in the context of data and humans.
基金supported in part by “the Ministry of Science and Technology of Taiwan” under Grant MOST 102-2221-E-009-083MY3, Grant MOST 103-2221-E-009-122-MY3, and Grant MOST 104-2221-E-009-051-MY3
文摘An evacuation plan helps people move away from an area or a building. To assist rapid evacuation,we present an algorithm to compute the optimal route for each local region. The idea is to reduce congestion and maximize the number of evacuees arriving at exits in each time span. Our system considers crowd distribution, exit locations, and corridor widths when determining optimal routes. It also simulates crowd movements during route optimization. As a basis,we expect that neighboring crowds who take different evacuation routes should arrive at respective exits at nearly the same time. If this is not the case, our system updates the routes of the slower crowds. As crowd simulation is non-linear, the optimal route is computed in an iterative manner. The system repeats until an optimal state is achieved. In addition to directly computing optimal routes for a situation, our system allows the structure of the situation to be decomposed,and determines the routes in a hierarchical manner.This strategy not only reduces the computational cost but also enables crowds in different regions to evacuate with different priorities. Experimental results,with visualizations, demonstrate the feasibility of our evacuation route optimization method.
