DocumentCode :
3334968
Title :
Visual Segmentation-Based Data Record Extraction from Web Documents
Author :
Longzhuang Li ; Yonghuai Liu ; Obregon, A.
Author_Institution :
Texas A&M Univ., Corpus Christi
fYear :
2007
fDate :
13-15 Aug. 2007
Firstpage :
502
Lastpage :
507
Abstract :
Semi-structured data records contained in the Web pages provide useful information for shopping agents and metasearch engines. In this paper, we present a visual segmentation-based data record extraction (VSDR) method to extract data records from those Web pages. VSDR method first segments a Web page into semantic blocks using the spatial closeness and visual resemblance of data records, then neighboring and non-neighboring data records are extracted based on a compress and collapse technique. Experimental results slum that unlike the existing methods which only generate good results on their test domains, VSDR is a general data record extraction method that is able to produce quite stable and good results on a wide range of Web pages.
Keywords :
Internet; document image processing; information retrieval; Web documents; metasearch engines; semi-structured data records; visual resemblance; visual segmentation-based data record extraction; Computer science; Data mining; Databases; Engines; HTML; Humans; Metasearch; Navigation; Partitioning algorithms; Web pages;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Reuse and Integration, 2007. IRI 2007. IEEE International Conference on
Conference_Location :
Las Vegas, IL
Print_ISBN :
1-4244-1500-4
Electronic_ISBN :
1-4244-1500-4
Type :
conf
DOI :
10.1109/IRI.2007.4296670
Filename :
4296670
Link To Document :
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