NDLI: Semantic HTML Page Segmentation using Type Analysis

Content Provider	IEEE Xplore Digital Library
Author	Xin Yang Peifeng Xiang Yuanchun Shi
Copyright Year	2006
Description	Author affiliation: Dept. of Comput. Sci. & Technol., Tsinghua Univ., Beijing (Xin Yang; Peifeng Xiang; Yuanchun Shi)
Abstract	Semantic information is necessary for semantic Web processing and is useful to Web adaptation services such as personalization of users' browsing activities on small screen devices. However, semantic information is always implicitly encoded in most existing HTML documents. This paper describes a page segmentation method to parse Web pages into rectangular segments containing some semantic information, namely blocks. Existing page segmentation techniques are mainly built on HTML DOM structure or purely vision based, not accurate enough either in visual presentation or in semantic sense. Our approach is automatic, and based on a refined typing system which tightly couples type analysis with indispensable visual cues to generate blocks into the tree structure, aiming to achieve high degree of coherence in both semantic and visual views. Experimental results show better accuracy and completeness of our method over existing ones
Starting Page	669
Ending Page	674
File Size	7372115
Page Count	6
File Format	PDF
ISBN	1424403251
DOI	10.1109/SPCA.2006.297506
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-08-03
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Pervasive computing Tree data structures Filtering Particle separators Visual Cues HTML Application software Stress Semantic Web Computer science Web pages Type Recognition Page Segmentation Block Semantic Structural Tree Pattern Discovery
Content Type	Text
Resource Type	Article

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