Improving pseudo-relevance feedback in web information retrieval using web page segmentation

Shipeng Yu; Deng Cai; Ji-Rong Wen; Wei-Ying Ma

doi:10.1145/775152.775155

Improving pseudo-relevance feedback in web information retrieval using web page segmentation

Shipeng Yu
, Deng Cai
, Ji-Rong Wen
, Wei-Ying Ma

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

212 Citations (Scopus)

Abstract

In contrast to traditional document retrieval, a web page as a whole is not a good information unit to search because it often contains multiple topics and a lot of irrelevant information from navigation, decoration, and interaction part of the page. In this paper, we propose a VIsion-based Page Segmentation (VIPS) algorithm to detect the semantic content structure in a web page. Compared with simple DOM based segmentation method, our page segmentation scheme utilizes useful visual cues to obtain a better partition of a page at the semantic level. By using our VIPS algorithm to assist the selection of query expansion terms in pseudo-relevance feedback in web information retrieval, we achieve 27% performance improvement on Web Track dataset.
Copyright is held by the author/owner(s).

Original language	English
Title of host publication	Proceedings of the 12th International Conference on World Wide Web, WWW 2003
Pages	11-18
DOIs	https://doi.org/10.1145/775152.775155
Publication status	Published - 2003
Externally published	Yes
Event	12th International Conference on World Wide Web, WWW 2003 - Budapest, Hungary Duration: 20 May 2003 → 24 May 2003

Publication series

Name	Proceedings of the 12th International Conference on World Wide Web, WWW 2003

Conference

Conference	12th International Conference on World Wide Web, WWW 2003
Place	Hungary
City	Budapest
Period	20/05/03 → 24/05/03

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

page segmentation
query expansion
relevance feedback
web information retrieval

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10.1145/775152.775155

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@inproceedings{3b6616d3b7a7445ca4f04bb81226fe2e,

title = "Improving pseudo-relevance feedback in web information retrieval using web page segmentation",

abstract = "In contrast to traditional document retrieval, a web page as a whole is not a good information unit to search because it often contains multiple topics and a lot of irrelevant information from navigation, decoration, and interaction part of the page. In this paper, we propose a VIsion-based Page Segmentation (VIPS) algorithm to detect the semantic content structure in a web page. Compared with simple DOM based segmentation method, our page segmentation scheme utilizes useful visual cues to obtain a better partition of a page at the semantic level. By using our VIPS algorithm to assist the selection of query expansion terms in pseudo-relevance feedback in web information retrieval, we achieve 27\% performance improvement on Web Track dataset. Copyright is held by the author/owner(s).",

keywords = "page segmentation, query expansion, relevance feedback, web information retrieval",

author = "Shipeng Yu and Deng Cai and Ji-Rong Wen and Wei-Ying Ma",

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].; 12th International Conference on World Wide Web, WWW 2003 ; Conference date: 20-05-2003 Through 24-05-2003",

year = "2003",

doi = "10.1145/775152.775155",

language = "English",

isbn = "1581136803",

series = "Proceedings of the 12th International Conference on World Wide Web, WWW 2003",

pages = "11--18",

booktitle = "Proceedings of the 12th International Conference on World Wide Web, WWW 2003",

}

Yu, S, Cai, D, Wen, J-R & Ma, W-Y 2003, Improving pseudo-relevance feedback in web information retrieval using web page segmentation. in Proceedings of the 12th International Conference on World Wide Web, WWW 2003. Proceedings of the 12th International Conference on World Wide Web, WWW 2003, pp. 11-18, 12th International Conference on World Wide Web, WWW 2003, Budapest, Hungary, 20/05/03. https://doi.org/10.1145/775152.775155

Improving pseudo-relevance feedback in web information retrieval using web page segmentation. / Yu, Shipeng; Cai, Deng; Wen, Ji-Rong et al.
Proceedings of the 12th International Conference on World Wide Web, WWW 2003. 2003. p. 11-18 (Proceedings of the 12th International Conference on World Wide Web, WWW 2003).

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

TY - GEN

T1 - Improving pseudo-relevance feedback in web information retrieval using web page segmentation

AU - Yu, Shipeng

AU - Cai, Deng

AU - Wen, Ji-Rong

AU - Ma, Wei-Ying

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 - 2003

Y1 - 2003

N2 - In contrast to traditional document retrieval, a web page as a whole is not a good information unit to search because it often contains multiple topics and a lot of irrelevant information from navigation, decoration, and interaction part of the page. In this paper, we propose a VIsion-based Page Segmentation (VIPS) algorithm to detect the semantic content structure in a web page. Compared with simple DOM based segmentation method, our page segmentation scheme utilizes useful visual cues to obtain a better partition of a page at the semantic level. By using our VIPS algorithm to assist the selection of query expansion terms in pseudo-relevance feedback in web information retrieval, we achieve 27% performance improvement on Web Track dataset. Copyright is held by the author/owner(s).

AB - In contrast to traditional document retrieval, a web page as a whole is not a good information unit to search because it often contains multiple topics and a lot of irrelevant information from navigation, decoration, and interaction part of the page. In this paper, we propose a VIsion-based Page Segmentation (VIPS) algorithm to detect the semantic content structure in a web page. Compared with simple DOM based segmentation method, our page segmentation scheme utilizes useful visual cues to obtain a better partition of a page at the semantic level. By using our VIPS algorithm to assist the selection of query expansion terms in pseudo-relevance feedback in web information retrieval, we achieve 27% performance improvement on Web Track dataset. Copyright is held by the author/owner(s).

KW - page segmentation

KW - query expansion

KW - relevance feedback

KW - web information retrieval

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DO - 10.1145/775152.775155

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

SN - 1581136803

SN - 9781581136807

T3 - Proceedings of the 12th International Conference on World Wide Web, WWW 2003

SP - 11

EP - 18

BT - Proceedings of the 12th International Conference on World Wide Web, WWW 2003

T2 - 12th International Conference on World Wide Web, WWW 2003

Y2 - 20 May 2003 through 24 May 2003

ER -

Improving pseudo-relevance feedback in web information retrieval using web page segmentation

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Research Keywords

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