Interactive Visual Overviews of Large Multi-Dimensional Datasets
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Description: Exploratory data analysis through machine learning and visualization. Work from AIRL, Dept. of CS, Iowa State University.
Interactive Visual Overviews of Large, Multi-Dimensional Datasets Artificial Intelligence Research Laboratory Interactive Visual Overviews of Large Multi-Dimensional Datasets Recent advances in high throughput data acquisition, digital storage, computer and communications technologies have made it possible to gather, store, and transmit large volumes of data. Translating the advances in data acquisition and storage technologies into fundamental gains in understanding of the respective domains, requires the development of sophisticated computational tools to assist in the knowledge discovery process. Given the large volumes of data, and the broad range of scientifically relevant and potentially complex interrelationships that might be of interest, machine learning or data mining algorithms offer one of the most practical and cost-effective approaches to data-driven knowledge discovery. However, fully automated knowledge discovery is beyond the current state of the art in artificial intelligence, and we still need the "little-understood ability of human beings to `see the big picture' and `know where to look' when presented with visual data". The proposed research seeks to develop sophisticated dynamic graphics tools for interactive exploratory analysis of very large datasets. These tools, when used in conjunction with data mining algorithms, will enable the user to overview the data space as well as the complex relationships discovered by the data mining algorithms. This would significantly enhance the utility of machine learning algorithms for interactive data-driven knowledge discovery from large, high dimensional datasets. The proposed research brings together a team of researchers with complementary research interests and expertise in statistics and visualization, artificial intelligence, machine learning, and bioinformatics, databases and information management to develop a modular and extensible software toolbox for user-driven, computer-assisted, interactive exploration of extremely larg
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| Page title: | Interactive Visual Overviews of Large, Multi-Dimensional Datasets |
| Keywords: | Artificial Intelligence, Cognitive Science, Neural Networks, Autonomous Robots, Automata Induction, Computational Learning Theory, Computational Organizational Theory, Data Mining, Knowledge Discovery, Visualization, Decision Support Systems, Distributed Knowledge Networks, Intelligent Agents, Mobile Agents, and Multi-Agent Systems, Knowledge Representation, Exploratory Data Analysis, Inference, Machine Learning, Parallel and Distributed AI, Biological Computation, Computational Neuroscience; Evolutionary, Cellular, and Neural Computation, Bioinformatics, Computational Biology, Genetic Regulatory Networks, Protein Structure-Function Prediction, Computational Genomics, Metabolic Pathways, Distributed Knowledge Networks for Bioinformatics, Complex Adaptive Systems, Network Information Systems, Distributed Knowledge Networks, Distributed Databases, Mediators, Data Warehouses, Intelligent Agents, Mobile Agents, Multi-Agent Systems, Diagnosis, Complex Systems Monitoring and Control, Intrusion Detection, honavar, vasant honavar |
| Description: | Information on current research, courses, and publications of the Artificial Intelligence Research Laboratory at Iowa State University |
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| Date | activated: 22-Jun-1987 last updated: 22-May-2013 expires: 31-Jul-2014 |