A web page segmentation approach using visual semantics

Jun Zeng, Brendan Flanagan, Sachio Hirokawa, Eisuke Ito

    研究成果: ジャーナルへの寄稿学術誌査読

    3 被引用数 (Scopus)


    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.

    ジャーナルIEICE Transactions on Information and Systems
    出版ステータス出版済み - 2014

    !!!All Science Journal Classification (ASJC) codes

    • ソフトウェア
    • ハードウェアとアーキテクチャ
    • コンピュータ ビジョンおよびパターン認識
    • 電子工学および電気工学
    • 人工知能


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