Hierarchical clustering of WWW image search results using visual, textual and link information

Deng Cai; Xiaofei He; Zhiwei Li; Wei-Ying Ma; Ji-Rong Wen

doi:10.1145/1027527.1027747

Hierarchical clustering of WWW image search results using visual, textual and link information

Deng Cai
, Xiaofei He
, Zhiwei Li
, Wei-Ying Ma
, Ji-Rong Wen

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

283 Citations (Scopus)

Abstract

We consider the problem of clustering Web image search results. Generally, the image search results returned by an image search engine contain multiple topics. Organizing the results into different semantic clusters facilitates users' browsing. In this paper, we propose a hierarchical clustering method using visual, textual and link analysis. By using a vision-based page segmentation algorithm, a web page is partitioned into blocks, and the textual and link information of an image can be accurately extracted from the block containing that image. By using block-level link analysis techniques, an image graph can be constructed. We then apply spectral techniques to find a Euclidean embedding of the images which respects the graph structure, Thus for each image, we have three kinds of representations, i.e. visual feature based representation, textual feature based representation and graph based representation. Using spectral clustering techniques, we can cluster the search results into different semantic clusters. An image search example illustrates the potential of these techniques.
Copyright 2004 ACM

Original language	English
Title of host publication	ACM Multimedia 2004 - proceedings of the 12th ACM International Conference on Multimedia
Publisher	Association for Computing Machinery
Pages	952-959
ISBN (Print)	1581138938, 9781581138931
DOIs	https://doi.org/10.1145/1027527.1027747
Publication status	Published - 2004
Externally published	Yes
Event	ACM Multimedia 2004 - proceedings of the 12th ACM International Conference on Multimedia - New York, NY, United States Duration: 10 Oct 2004 → 16 Oct 2004

Publication series

Name	ACM Multimedia 2004 - proceedings of the 12th ACM International Conference on Multimedia

Conference

Conference	ACM Multimedia 2004 - proceedings of the 12th ACM International Conference on Multimedia
Place	United States
City	New York, NY
Period	10/10/04 → 16/10/04

Bibliographical note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

Research Keywords

Graph Model
Image Clustering
Link Analysis
Search Result Organization
Spectral Analysis
Vision Based Page Segmentation
Web Image Search

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10.1145/1027527.1027747

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Cai, D., He, X., Li, Z., Ma, W.-Y., & Wen, J.-R. (2004). Hierarchical clustering of WWW image search results using visual, textual and link information. In ACM Multimedia 2004 - proceedings of the 12th ACM International Conference on Multimedia (pp. 952-959). (ACM Multimedia 2004 - proceedings of the 12th ACM International Conference on Multimedia). Association for Computing Machinery. https://doi.org/10.1145/1027527.1027747

Cai, Deng ; He, Xiaofei ; Li, Zhiwei et al. / Hierarchical clustering of WWW image search results using visual, textual and link information. ACM Multimedia 2004 - proceedings of the 12th ACM International Conference on Multimedia. Association for Computing Machinery, 2004. pp. 952-959 (ACM Multimedia 2004 - proceedings of the 12th ACM International Conference on Multimedia).

@inproceedings{e2c780eb7e1644da8f9b48ad3598e6cd,

title = "Hierarchical clustering of WWW image search results using visual, textual and link information",

abstract = "We consider the problem of clustering Web image search results. Generally, the image search results returned by an image search engine contain multiple topics. Organizing the results into different semantic clusters facilitates users' browsing. In this paper, we propose a hierarchical clustering method using visual, textual and link analysis. By using a vision-based page segmentation algorithm, a web page is partitioned into blocks, and the textual and link information of an image can be accurately extracted from the block containing that image. By using block-level link analysis techniques, an image graph can be constructed. We then apply spectral techniques to find a Euclidean embedding of the images which respects the graph structure, Thus for each image, we have three kinds of representations, i.e. visual feature based representation, textual feature based representation and graph based representation. Using spectral clustering techniques, we can cluster the search results into different semantic clusters. An image search example illustrates the potential of these techniques. Copyright 2004 ACM",

keywords = "Graph Model, Image Clustering, Link Analysis, Search Result Organization, Spectral Analysis, Vision Based Page Segmentation, Web Image Search",

author = "Deng Cai and Xiaofei He and Zhiwei Li and Wei-Ying Ma and Ji-Rong Wen",

note = "Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].; ACM Multimedia 2004 - proceedings of the 12th ACM International Conference on Multimedia ; Conference date: 10-10-2004 Through 16-10-2004",

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doi = "10.1145/1027527.1027747",

language = "English",

isbn = "1581138938",

series = "ACM Multimedia 2004 - proceedings of the 12th ACM International Conference on Multimedia",

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Cai, D, He, X, Li, Z, Ma, W-Y & Wen, J-R 2004, Hierarchical clustering of WWW image search results using visual, textual and link information. in ACM Multimedia 2004 - proceedings of the 12th ACM International Conference on Multimedia. ACM Multimedia 2004 - proceedings of the 12th ACM International Conference on Multimedia, Association for Computing Machinery, pp. 952-959, ACM Multimedia 2004 - proceedings of the 12th ACM International Conference on Multimedia, New York, NY, United States, 10/10/04. https://doi.org/10.1145/1027527.1027747

Hierarchical clustering of WWW image search results using visual, textual and link information. / Cai, Deng; He, Xiaofei; Li, Zhiwei et al.
ACM Multimedia 2004 - proceedings of the 12th ACM International Conference on Multimedia. Association for Computing Machinery, 2004. p. 952-959 (ACM Multimedia 2004 - proceedings of the 12th ACM International Conference on Multimedia).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Hierarchical clustering of WWW image search results using visual, textual and link information

AU - Cai, Deng

AU - He, Xiaofei

AU - Li, Zhiwei

AU - Ma, Wei-Ying

AU - Wen, Ji-Rong

N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

PY - 2004

Y1 - 2004

N2 - We consider the problem of clustering Web image search results. Generally, the image search results returned by an image search engine contain multiple topics. Organizing the results into different semantic clusters facilitates users' browsing. In this paper, we propose a hierarchical clustering method using visual, textual and link analysis. By using a vision-based page segmentation algorithm, a web page is partitioned into blocks, and the textual and link information of an image can be accurately extracted from the block containing that image. By using block-level link analysis techniques, an image graph can be constructed. We then apply spectral techniques to find a Euclidean embedding of the images which respects the graph structure, Thus for each image, we have three kinds of representations, i.e. visual feature based representation, textual feature based representation and graph based representation. Using spectral clustering techniques, we can cluster the search results into different semantic clusters. An image search example illustrates the potential of these techniques. Copyright 2004 ACM

AB - We consider the problem of clustering Web image search results. Generally, the image search results returned by an image search engine contain multiple topics. Organizing the results into different semantic clusters facilitates users' browsing. In this paper, we propose a hierarchical clustering method using visual, textual and link analysis. By using a vision-based page segmentation algorithm, a web page is partitioned into blocks, and the textual and link information of an image can be accurately extracted from the block containing that image. By using block-level link analysis techniques, an image graph can be constructed. We then apply spectral techniques to find a Euclidean embedding of the images which respects the graph structure, Thus for each image, we have three kinds of representations, i.e. visual feature based representation, textual feature based representation and graph based representation. Using spectral clustering techniques, we can cluster the search results into different semantic clusters. An image search example illustrates the potential of these techniques. Copyright 2004 ACM

KW - Graph Model

KW - Image Clustering

KW - Link Analysis

KW - Search Result Organization

KW - Spectral Analysis

KW - Vision Based Page Segmentation

KW - Web Image Search

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U2 - 10.1145/1027527.1027747

DO - 10.1145/1027527.1027747

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 1581138938

SN - 9781581138931

T3 - ACM Multimedia 2004 - proceedings of the 12th ACM International Conference on Multimedia

SP - 952

EP - 959

BT - ACM Multimedia 2004 - proceedings of the 12th ACM International Conference on Multimedia

PB - Association for Computing Machinery

T2 - ACM Multimedia 2004 - proceedings of the 12th ACM International Conference on Multimedia

Y2 - 10 October 2004 through 16 October 2004

ER -

Cai D, He X, Li Z, Ma WY, Wen JR. Hierarchical clustering of WWW image search results using visual, textual and link information. In ACM Multimedia 2004 - proceedings of the 12th ACM International Conference on Multimedia. Association for Computing Machinery. 2004. p. 952-959. (ACM Multimedia 2004 - proceedings of the 12th ACM International Conference on Multimedia). doi: 10.1145/1027527.1027747

Hierarchical clustering of WWW image search results using visual, textual and link information

Abstract

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Research Keywords

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