Readings in information visualization: using vision to think
Readings in information visualization: using vision to think
Visual exploration of large data sets
Communications of the ACM
The Eyes Have It: A Task by Data Type Taxonomy for Information Visualizations
VL '96 Proceedings of the 1996 IEEE Symposium on Visual Languages
Information Visualization: Perception for Design
Information Visualization: Perception for Design
IEEE Computer Graphics and Applications
Challenges in Visual Data Analysis
IV '06 Proceedings of the conference on Information Visualization
Information Visualization: Design for Interaction (2nd Edition)
Information Visualization: Design for Interaction (2nd Edition)
Information Visualization: Beyond the Horizon
Information Visualization: Beyond the Horizon
Geovisual analytics for spatial decision support: Setting the research agenda
International Journal of Geographical Information Science - Geovisual Analytics for Spatial Decision Support
A PROMISE for experimental evaluation
CLEF'10 Proceedings of the 2010 international conference on Multilingual and multimodal information access evaluation: cross-language evaluation forum
| Hi-index | 0.00 |
Visual Analytics (VA) [1] is an emerging multi-disciplinary area that takes into account both ad-hoc and classical Data Mining (DM) algorithms and Information Visualization IV (IV) techniques, combining the strengths of human and electronic data processing. Visualisation becomes the medium of a semi-automated analytical process, where human beings and machines cooperate using their respective distinct capabilities for the most effective results. Decisions on which direction analysis should take in order to accomplish a certain task are left to the user. Although IV techniques have been extensively explored [2], combining them with automated data analysis for specific application domains is still a challenging activity [3]. This chapter provides an introduction of the main concepts behind VA and presents some practical examples on how apply it to Information Retrieval (IR).