Michael Bui's research while affiliated with The University of Sydney and other places
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Publications (4)
The Self-Organizing Maps (SOMs) are popular artificial neural networks that are often used for data analyses through clustering
and visualisation. SOM’s mathematical model is inherently parallel. However, many implementations have not successfully exploited
its parallelism because previous attempts often required cluster-like infrastructures. This...
Spatialization methods create visualizations that allow users to analyze high-dimensional data in an intuitive manner and
facilitates the extraction of meaningful information. Just as geographic maps are simplified representations of geographic
spaces, these visualizations are essentially maps of abstract data spaces that are created through dimens...
Data visualization has become an important tool for analyzing very complex data. In particular, spatial visualization enables users to view data in a intuitive manner. It has typically been used to externalize clusters and their relationships which exist in highly complex multidimensional data. We envisage that not only cluster formation and relati...
The complexity and size of data is rapidly increasing in modern science, business and engineering. This has resulted in increasing demands for more sophisticated data analysis methods. Multidimensional scaling has been used to visualize large high-dimensional datasets in the form of a map. Such maps are very intuitive for us, as we are familiar wit...
Citations
... In fact, due to the simplicity of the training algorithm and since training data need only be sent once to the training algorithm to update the nodal weights of the whole map, the training algorithm can be implemented for execution in GPU with at most two communications between CPU and GPU. The performance improvements of such implementations have been widely demonstrated in literature [40,41]. ...
... Previous research with SOM and LVQ analysis on GIS has been oriented to multidimensional geographic data visualization (Takatsuka, 2001;Bui and Takatsuka, 2009) and identification of spatial features by unsupervised clustering (Bação, Lobo, and Painho, 2004; Buea and Stepinskib, 2006;Henriques, Bação, and Lobo, 2009). Specific implementations of SOM for these GIS applications and some variants has been proposed by Bação, Lobo, and Painho (2005b). ...
... We are not the first to consider this type of path-analysis on a SOM. As Bui and Takatsuka (2007) describe, " we envisage that if an abstract knowledge space can be represented in the form of a map, transitions of knowledge can be defined as a path on this map. " Because our abstract knowledge space is the English language (in vector form), " transitions of knowledge " are conceptual differences in words. ...
