Visualisation of heterogeneous data with the generalised generative topographic mapping

Michel Randrianandrasana; Shahzad Mumtaz; Ian Nabney

Visualisation of heterogeneous data with the generalised generative topographic mapping

Michel Randrianandrasana, Shahzad Mumtaz, Ian Nabney

Computer Science Research Group

Research output: Chapter in Book/Published conference output › Conference publication

Abstract

Heterogeneous and incomplete datasets are common in many real-world visualisation applications. The probabilistic nature of the Generative Topographic Mapping (GTM), which was originally developed for complete continuous data, can be extended to model heterogeneous (i.e. containing both continuous and discrete values) and missing data. This paper describes and assesses the resulting model on both synthetic and real-world heterogeneous data with missing values.

Original language	English
Title of host publication	Proceedings of the 6th international conference on information visualization theory and applications
Editors	José Braz, Andreas Kerren, Lars Linsen
Publisher	SciTePress
Pages	233-238
Number of pages	6
ISBN (Print)	978-989-758-088-8
Publication status	Published - 2015
Event	6th International Conference on Information Visualization Theory and Applications - Berlin, Germany Duration: 11 Mar 2015 → 14 Mar 2015

Conference

Conference	6th International Conference on Information Visualization Theory and Applications
Abbreviated title	IVAPP 2015
Country/Territory	Germany
City	Berlin
Period	11/03/15 → 14/03/15

Keywords

data visualisation
heterogeneous and missing data
GTM
LTM

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Visualisation of heterogeneous data with the generalised generative topographic mapping
Presented at IVAPP 2015
Accepted author manuscript, 871 KBLicence: CC BY 3.0

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Randrianandrasana, M., Mumtaz, S., & Nabney, I. (2015). Visualisation of heterogeneous data with the generalised generative topographic mapping. In J. Braz, A. Kerren, & L. Linsen (Eds.), Proceedings of the 6th international conference on information visualization theory and applications (pp. 233-238). Article 28 SciTePress. http://www.scitepress.org/Portal/PublicationsDetail.aspx?ID=hna616hBT3k=&t=1

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title = "Visualisation of heterogeneous data with the generalised generative topographic mapping",

abstract = "Heterogeneous and incomplete datasets are common in many real-world visualisation applications. The probabilistic nature of the Generative Topographic Mapping (GTM), which was originally developed for complete continuous data, can be extended to model heterogeneous (i.e. containing both continuous and discrete values) and missing data. This paper describes and assesses the resulting model on both synthetic and real-world heterogeneous data with missing values.",

keywords = "data visualisation , heterogeneous and missing data, GTM, LTM",

author = "Michel Randrianandrasana and Shahzad Mumtaz and Ian Nabney",

year = "2015",

language = "English",

isbn = " 978-989-758-088-8",

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booktitle = "Proceedings of the 6th international conference on information visualization theory and applications",

publisher = "SciTePress",

note = "6th International Conference on Information Visualization Theory and Applications, IVAPP 2015 ; Conference date: 11-03-2015 Through 14-03-2015",

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Randrianandrasana, M, Mumtaz, S & Nabney, I 2015, Visualisation of heterogeneous data with the generalised generative topographic mapping. in J Braz, A Kerren & L Linsen (eds), Proceedings of the 6th international conference on information visualization theory and applications., 28, SciTePress, pp. 233-238, 6th International Conference on Information Visualization Theory and Applications, Berlin, Germany, 11/03/15. <http://www.scitepress.org/Portal/PublicationsDetail.aspx?ID=hna616hBT3k=&t=1>

Visualisation of heterogeneous data with the generalised generative topographic mapping. / Randrianandrasana, Michel; Mumtaz, Shahzad; Nabney, Ian.
Proceedings of the 6th international conference on information visualization theory and applications. ed. / José Braz; Andreas Kerren; Lars Linsen. SciTePress, 2015. p. 233-238 28.

Research output: Chapter in Book/Published conference output › Conference publication

TY - GEN

T1 - Visualisation of heterogeneous data with the generalised generative topographic mapping

AU - Randrianandrasana, Michel

AU - Mumtaz, Shahzad

AU - Nabney, Ian

PY - 2015

Y1 - 2015

N2 - Heterogeneous and incomplete datasets are common in many real-world visualisation applications. The probabilistic nature of the Generative Topographic Mapping (GTM), which was originally developed for complete continuous data, can be extended to model heterogeneous (i.e. containing both continuous and discrete values) and missing data. This paper describes and assesses the resulting model on both synthetic and real-world heterogeneous data with missing values.

AB - Heterogeneous and incomplete datasets are common in many real-world visualisation applications. The probabilistic nature of the Generative Topographic Mapping (GTM), which was originally developed for complete continuous data, can be extended to model heterogeneous (i.e. containing both continuous and discrete values) and missing data. This paper describes and assesses the resulting model on both synthetic and real-world heterogeneous data with missing values.

KW - data visualisation

KW - heterogeneous and missing data

KW - GTM

KW - LTM

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M3 - Conference publication

AN - SCOPUS:84938796633

SN - 978-989-758-088-8

SP - 233

EP - 238

BT - Proceedings of the 6th international conference on information visualization theory and applications

A2 - Braz, José

A2 - Kerren, Andreas

A2 - Linsen, Lars

PB - SciTePress

T2 - 6th International Conference on Information Visualization Theory and Applications

Y2 - 11 March 2015 through 14 March 2015

ER -

Visualisation of heterogeneous data with the generalised generative topographic mapping

Abstract

Conference

Keywords

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