A survey of visual analytics techniques for machine learning
Visual analytics for machine learning has recently evolved as one of the most exciting areas
in the field of visualization. To better identify which research topics are promising and to …
in the field of visualization. To better identify which research topics are promising and to …
Multi-feature, multi-modal, and multi-source social event detection: A comprehensive survey
The tremendous growth of event dissemination over social networks makes it very
challenging to accurately discover and track exciting events, as well as their evolution and …
challenging to accurately discover and track exciting events, as well as their evolution and …
A survey of urban visual analytics: Advances and future directions
Developing effective visual analytics systems demands care in characterization of domain
problems and integration of visualization techniques and computational models. Urban …
problems and integration of visualization techniques and computational models. Urban …
Forty years of research on factors influencing ethical decision making: Establishing a future research agenda
The purpose of this study is to review, synthesize and critique the voluminous,
multidisciplinary literature on factors influencing ethical decision making (EDM) by adopting …
multidisciplinary literature on factors influencing ethical decision making (EDM) by adopting …
Recent research advances on interactive machine learning
Interactive machine learning (IML) is an iterative learning process that tightly couples a
human with a machine learner, which is widely used by researchers and practitioners to …
human with a machine learner, which is widely used by researchers and practitioners to …
VIS+ AI: integrating visualization with artificial intelligence for efficient data analysis
Visualization and artificial intelligence (AI) are well-applied approaches to data analysis. On
one hand, visualization can facilitate humans in data understanding through intuitive visual …
one hand, visualization can facilitate humans in data understanding through intuitive visual …
A survey of big data dimensions vs social networks analysis
The pervasive diffusion of Social Networks (SN) produced an unprecedented amount of
heterogeneous data. Thus, traditional approaches quickly became unpractical for real life …
heterogeneous data. Thus, traditional approaches quickly became unpractical for real life …
Compass: Towards better causal analysis of urban time series
The spatial time series generated by city sensors allow us to observe urban phenomena like
environmental pollution and traffic congestion at an unprecedented scale. However …
environmental pollution and traffic congestion at an unprecedented scale. However …
ConceptExplorer: Visual analysis of concept drifts in multi-source time-series data
Time-series data is widely studied in various scenarios, like weather forecast, stock market,
customer behavior analysis. To comprehensively learn about the dynamic environments, it is …
customer behavior analysis. To comprehensively learn about the dynamic environments, it is …
[HTML][HTML] Space–time series clustering: Algorithms, taxonomy, and case study on urban smart cities
This paper provides a short overview of space–time series clustering, which can be
generally grouped into three main categories such as: hierarchical, partitioning-based, and …
generally grouped into three main categories such as: hierarchical, partitioning-based, and …