Information Visualization in Data Mining and Knowledge Discovery
By Usama M. Fayyad, G. Grinstein, Andreas Wierse. 2001
663 citations recorded by the source corpus.
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- Francisco Herrera
- Salvador Garcia
- Francisco Charte
- M. J. Jesús
- Alberto Fernández
- David Charte
- Josua Krause
- Adam Perer
Citations in the corpus
- A practical tutorial on autoencoders for nonlinear feature fusion: Taxonomy, models, software and guidelines (2018, background): “t fast search of similar images in databases. 5.5. Data visualization Understanding the nature of a given dataset can be a complex task when it posesses many dimensions. Data visualization techniques [136] can help analyze the structure of the data. One way of visualizing all instances in a dataset ”
- State-of-the-Art and Future Challenges in the Integration of Biobank Catalogues (2015, background): “Visual data exploration methods on large data sets were described by several authors, and particularly Keim [17], Hege et al. [18], Fayyad, Wierse and Grinstein [19], Fekete and Plaisant [20], and Santos and Brodlie [21] provide a good introduction to this topic.”
- Visualizations of Deep Neural Networks in Computer Vision: A Survey (2017, background): “However, understanding and trust have been identified as desirable property of data mining models [65].”
- Analysis of biomedical data with multilevel glyphs (2014, background): “(2001) [22], Fayyad, Wierse & Grinstein (2002), [23], Fekete & Plaisant (2002) [24], and Santos & Brodlie (2004) [25] provide a good introduction to this topic.”
- A Brief Survey of Text Mining (2005, unknown): “Hence we have a sequential classification problem for the labels of each word, with the surrounding words as input feature vector.”
- Building a Recommender Agent for e-Learning Systems (2002, background): “In this latter case visualization becomes part of data mining as an interactive process [10].”
- Interacting with Predictions: Visual Inspection of Black-box Machine Learning Models (2016, background): “[5]) and how the input is propagated (Correa et al.”