Web page organization and visualization using generative topographic mapping: A pilot study

Xiao-Feng Zhang; Chak-Man Lam; Kwok Wai Cheung

Web page organization and visualization using generative topographic mapping: A pilot study

Xiao-Feng Zhang, Chak-Man Lam, Kwok Wai Cheung

Department of Computer Science

Research output: Chapter in book/report/conference proceeding › Conference proceeding

Abstract

Automatic Web page organization and visualization is an effective way for foraging information in a Web structure. Web pages contain both text (content) and links (structure), implying that content and structure analysis techniques should be adopted and properly integrated. In this paper, we take the probabilistic model-based approach and extend a topographypreserving model known as Generative Topography Map (GTM). The extended GTM provides a principled way to integrate Web pages and hyperlinks and project them into a low-dimension latent space (2D in our case) for visualization. The proposed extension has been applied to the WebKB dataset. Based on the preliminary results obtained, we proposed several directions for future research.

Original language	English
Title of host publication	SRL2004: ICML 2004 Workshop on Statistical Relational Learning and its Connections to Other Fields. Accepted Papers
Pages	126-131
Number of pages	6
Publication status	Published - Jul 2004
Event	ICML 2004 Workshop on Statistical Relational Learning and its Connections to Other Fields (SRL 2004) - Banff, Canada Duration: 4 Jul 2004 → 8 Jul 2004

Conference

Conference	ICML 2004 Workshop on Statistical Relational Learning and its Connections to Other Fields (SRL 2004)
Period	4/07/04 → 8/07/04

User-Defined Keywords

Web page organization and visualization
Web content and structure analysis
Generative Topography Map

Cite this

@inproceedings{0378bf6bdd5841b29024f58c02840041,

title = "Web page organization and visualization using generative topographic mapping: A pilot study",

abstract = "Automatic Web page organization and visualization is an effective way for foraging information in a Web structure. Web pages contain both text (content) and links (structure), implying that content and structure analysis techniques should be adopted and properly integrated. In this paper, we take the probabilistic model-based approach and extend a topographypreserving model known as Generative Topography Map (GTM). The extended GTM provides a principled way to integrate Web pages and hyperlinks and project them into a low-dimension latent space (2D in our case) for visualization. The proposed extension has been applied to the WebKB dataset. Based on the preliminary results obtained, we proposed several directions for future research.",

keywords = "Web page organization and visualization, Web content and structure analysis, Generative Topography Map",

author = "Xiao-Feng Zhang and Chak-Man Lam and Cheung, {Kwok Wai}",

year = "2004",

month = jul,

language = "English",

pages = "126--131",

booktitle = "SRL2004: ICML 2004 Workshop on Statistical Relational Learning and its Connections to Other Fields. Accepted Papers",

note = "ICML 2004 Workshop on Statistical Relational Learning and its Connections to Other Fields (SRL 2004) ; Conference date: 04-07-2004 Through 08-07-2004",

}

Zhang, X-F, Lam, C-M & Cheung, KW 2004, Web page organization and visualization using generative topographic mapping: A pilot study. in SRL2004: ICML 2004 Workshop on Statistical Relational Learning and its Connections to Other Fields. Accepted Papers. pp. 126-131, ICML 2004 Workshop on Statistical Relational Learning and its Connections to Other Fields (SRL 2004), 4/07/04.

TY - GEN

T1 - Web page organization and visualization using generative topographic mapping: A pilot study

AU - Zhang, Xiao-Feng

AU - Lam, Chak-Man

AU - Cheung, Kwok Wai

PY - 2004/7

Y1 - 2004/7

N2 - Automatic Web page organization and visualization is an effective way for foraging information in a Web structure. Web pages contain both text (content) and links (structure), implying that content and structure analysis techniques should be adopted and properly integrated. In this paper, we take the probabilistic model-based approach and extend a topographypreserving model known as Generative Topography Map (GTM). The extended GTM provides a principled way to integrate Web pages and hyperlinks and project them into a low-dimension latent space (2D in our case) for visualization. The proposed extension has been applied to the WebKB dataset. Based on the preliminary results obtained, we proposed several directions for future research.

AB - Automatic Web page organization and visualization is an effective way for foraging information in a Web structure. Web pages contain both text (content) and links (structure), implying that content and structure analysis techniques should be adopted and properly integrated. In this paper, we take the probabilistic model-based approach and extend a topographypreserving model known as Generative Topography Map (GTM). The extended GTM provides a principled way to integrate Web pages and hyperlinks and project them into a low-dimension latent space (2D in our case) for visualization. The proposed extension has been applied to the WebKB dataset. Based on the preliminary results obtained, we proposed several directions for future research.

KW - Web page organization and visualization

KW - Web content and structure analysis

KW - Generative Topography Map

M3 - Conference proceeding

SP - 126

EP - 131

BT - SRL2004: ICML 2004 Workshop on Statistical Relational Learning and its Connections to Other Fields. Accepted Papers

T2 - ICML 2004 Workshop on Statistical Relational Learning and its Connections to Other Fields (SRL 2004)

Y2 - 4 July 2004 through 8 July 2004

ER -

Web page organization and visualization using generative topographic mapping: A pilot study

Abstract

Conference

User-Defined Keywords

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