presenter : chuang, kai-ting authors : guillaume cleuziou* 2013, prl
DESCRIPTION
OSOM: A method for building overlapping topological maps. Presenter : Chuang, Kai-Ting Authors : Guillaume Cleuziou* 2013, PRL. Outlines. Motivation Objectives Methodology Experiments Conclusions Comments. Motivation. - PowerPoint PPT PresentationTRANSCRIPT
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Intelligent Database Systems Lab
Presenter : Chuang, Kai-Ting
Authors : Guillaume Cleuziou*
2013, PRL
OSOM: A method for building overlapping topological maps
![Page 2: Presenter : Chuang, Kai-Ting Authors : Guillaume Cleuziou* 2013, PRL](https://reader035.vdocument.in/reader035/viewer/2022070411/56814702550346895db43cf1/html5/thumbnails/2.jpg)
Intelligent Database Systems Lab
Outlines Motivation Objectives Methodology Experiments Conclusions Comments
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Intelligent Database Systems Lab
Motivation• Overlapping clustering solutions extract data
organizations that are more fitted to the input data
than crisp clustering solutions.
• Unsupervised neural networks bring efficient
solutions to visualize class structures.
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Intelligent Database Systems Lab
Objectives• We present the algorithm O-SOM that uses both an
overlapping variant of the k-means clustering
algorithm and the well known Kohonen approach, in
order to build overlapping topologic maps.
• To solve problems that are recurrent in overlapping
clustering: number of clusters, complexity of the
algorithm and coherence of the overlaps.
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Methodology-Framework
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Intelligent Database Systems Lab
Methodology
OSOM SOM
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Intelligent Database Systems Lab
Methodolog-fast-osom
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Experiment-dataset
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Intelligent Database Systems Lab
Experiment-evaluation framework
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Experiment results
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Experiment-Topological evaluation
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Intelligent Database Systems Lab
Conclusions
• Ensure the algorithm to converge and then bring
solutions to the motivations mentioned: limited
complexity, topological correctness, etc.
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Intelligent Database Systems Lab
Comments• Advantages– The OSOM is simple method.
• Applications– Topological maps.