A Web Page Segmentation Approach Using Visual Semantics

作者：Zeng Jun^*; Flanagan Brendan; Hirokawa Sachio; Ito Eisuke

来源：IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, 2014, E97D(2): 223-230.

DOI：10.1587/transinf.E97.D.223

• web page segmentation
• visual semantics
• seam degree
• content similarity

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.

• 出版日期2014-2
• 单位重庆大学