相关论文: A Unified Comparison of User Modeling Techniques f…
Online crowdsourcing platforms have made it increasingly easy to perform evaluations of algorithm outputs with survey questions like "which image is better, A or B?", leading to their proliferation in vision and graphics research papers.…
With the rise of machines to human-level performance in complex recognition tasks, a growing amount of work is directed towards comparing information processing in humans and machines. These studies are an exciting chance to learn about one…
Climate science produces a wealth of complex, high-dimensional, multivariate data from observations and numerical models. These data are critical for understanding climate changes and their socioeconomic impacts. Climate scientists are…
Analysis of temporal network data arising from online interactive social experiments is not possible with standard statistical methods because the assumptions of these models, such as independence of observations, are not satisfied. In this…
Modern data is messy and high-dimensional, and it is often not clear a priori what are the right questions to ask. Instead, the analyst typically needs to use the data to search for interesting analyses to perform and hypotheses to test.…
Visual analytics (VA) tools support data exploration by helping analysts quickly and iteratively generate views of data which reveal interesting patterns. However, these tools seldom enable explicit checks of the resulting interpretations…
Media is evolving from traditional linear narratives to personalised experiences, where control over information (or how it is presented) is given to individual audience members. Measuring and understanding audience engagement with this…
With the proliferation of consumer virtual reality (VR) headsets and creative tools, content creators have started to experiment with new forms of interactive audience experience using immersive media. Understanding user attention and…
Visual search is an essential part of almost any everyday human goal-directed interaction with the environment. Nowadays, several algorithms are able to predict gaze positions during simple observation, but few models attempt to simulate…
There is a growing interest in designing tools to support interactivity specification and authoring in data visualization. To develop expressive and flexible tools, we need theories and models that describe the task space of interaction…
The integration of artificial intelligence (AI) into daily life, particularly through information retrieval and recommender systems, has necessitated advanced user modeling and profiling techniques to deliver personalized experiences. These…
In many areas of data mining, data is collected from humans beings. In this contribution, we ask the question of how people actually respond to ordinal scales. The main problem observed is that users tend to be volatile in their choices,…
As machine learning (ML) systems become increasingly widespread, it is necessary to audit these systems for biases prior to their deployment. Recent research has developed algorithms for effectively identifying intersectional bias in the…
With the servitization of business, understanding how users experience services becomes a crucial success factor for companies. Therefore, there is a need to include feedback from user experiences in the software engineering process.…
The collection of large, complex datasets has become common across a wide variety of domains. Visual analytics tools increasingly play a key role in exploring and answering complex questions about these large datasets. However, many…
User preference modeling is a vital yet challenging problem in personalized product search. In recent years, latent space based methods have achieved state-of-the-art performance by jointly learning semantic representations of products,…
A large body of work in behavioral fields attempts to develop models that describe the way people, as opposed to rational agents, make decisions. A recent Choice Prediction Competition (2015) challenged researchers to suggest a model that…
Data integration is often performed to consolidate information from multiple disparate data sources during visual data analysis. However, integration operations are usually separate from visual analytics operations such as encode and filter…
The rapid advances in Foundation Models and agentic Artificial Intelligence are transforming multimedia analytics by enabling richer, more sophisticated interactions between humans and analytical systems. Existing conceptual models for…
Many visualization techniques have been created to explain the behavior of computer vision models, but they largely consist of static diagrams that convey limited information. Interactive visualizations allow users to more easily interpret…