IEICE TRANSACTIONS on Information
A Web Page Segmentation Approach Using Visual Semantics
Summary :
Web page segmentation has a variety of benefits and potential web applications. Early techniques of web page segmentation are mainly based on machine learning algorithms and rule-based heuristics, which cannot be used for large-scale page segmentation. In this paper, we propose a formulated page segmentation method using visual semantics. Instead of analyzing the visual cues of web pages, this method utilizes three measures to formulate the visual semantics: layout tree is used to recognize the visual similar blocks; seam degree is used to describe how neatly the blocks are arranged; content similarity is used to describe the content coherent degree between blocks. A comparison experiment was done using the VIPS algorithm as a baseline. Experiment results show that the proposed method can divide a Web page into appropriate semantic segments.
- Publication
- IEICE TRANSACTIONS on Information Vol.E97-D No.2 pp.223-230
- Publication Date
- 2014/02/01
- Publicized
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.E97.D.223
- Type of Manuscript
- PAPER
- Category
- Data Engineering, Web Information Systems
Authors
Jun ZENG
Kyushu University
Brendan FLANAGAN
Kyushu University
Sachio HIROKAWA
Kyushu University
Eisuke ITO
Kyushu University
Keyword
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Jun ZENG, Brendan FLANAGAN, Sachio HIROKAWA, Eisuke ITO, "A Web Page Segmentation Approach Using Visual Semantics" in IEICE TRANSACTIONS on Information,
vol. E97-D, no. 2, pp. 223-230, February 2014, doi: 10.1587/transinf.E97.D.223.
Abstract: Web page segmentation has a variety of benefits and potential web applications. Early techniques of web page segmentation are mainly based on machine learning algorithms and rule-based heuristics, which cannot be used for large-scale page segmentation. In this paper, we propose a formulated page segmentation method using visual semantics. Instead of analyzing the visual cues of web pages, this method utilizes three measures to formulate the visual semantics: layout tree is used to recognize the visual similar blocks; seam degree is used to describe how neatly the blocks are arranged; content similarity is used to describe the content coherent degree between blocks. A comparison experiment was done using the VIPS algorithm as a baseline. Experiment results show that the proposed method can divide a Web page into appropriate semantic segments.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E97.D.223/_p
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@ARTICLE{e97-d_2_223,
author={Jun ZENG, Brendan FLANAGAN, Sachio HIROKAWA, Eisuke ITO, },
journal={IEICE TRANSACTIONS on Information},
title={A Web Page Segmentation Approach Using Visual Semantics},
year={2014},
volume={E97-D},
number={2},
pages={223-230},
abstract={Web page segmentation has a variety of benefits and potential web applications. Early techniques of web page segmentation are mainly based on machine learning algorithms and rule-based heuristics, which cannot be used for large-scale page segmentation. In this paper, we propose a formulated page segmentation method using visual semantics. Instead of analyzing the visual cues of web pages, this method utilizes three measures to formulate the visual semantics: layout tree is used to recognize the visual similar blocks; seam degree is used to describe how neatly the blocks are arranged; content similarity is used to describe the content coherent degree between blocks. A comparison experiment was done using the VIPS algorithm as a baseline. Experiment results show that the proposed method can divide a Web page into appropriate semantic segments.},
keywords={},
doi={10.1587/transinf.E97.D.223},
ISSN={1745-1361},
month={February},}
Copy
TY - JOUR
TI - A Web Page Segmentation Approach Using Visual Semantics
T2 - IEICE TRANSACTIONS on Information
SP - 223
EP - 230
AU - Jun ZENG
AU - Brendan FLANAGAN
AU - Sachio HIROKAWA
AU - Eisuke ITO
PY - 2014
DO - 10.1587/transinf.E97.D.223
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E97-D
IS - 2
JA - IEICE TRANSACTIONS on Information
Y1 - February 2014
AB - Web page segmentation has a variety of benefits and potential web applications. Early techniques of web page segmentation are mainly based on machine learning algorithms and rule-based heuristics, which cannot be used for large-scale page segmentation. In this paper, we propose a formulated page segmentation method using visual semantics. Instead of analyzing the visual cues of web pages, this method utilizes three measures to formulate the visual semantics: layout tree is used to recognize the visual similar blocks; seam degree is used to describe how neatly the blocks are arranged; content similarity is used to describe the content coherent degree between blocks. A comparison experiment was done using the VIPS algorithm as a baseline. Experiment results show that the proposed method can divide a Web page into appropriate semantic segments.
ER -
English
