Recognising Informative Web Page Blocks Using Visual Segmentation for Efficient Information Extraction

dc.creatorKang,Jinbeom
dc.creatorChoi,Joongmin
dc.date2008
dc.date.accessioned2024-02-06T12:56:40Z
dc.date.available2024-02-06T12:56:40Z
dc.descriptionAs web sites are getting more complicated, the construction of web information extraction systems becomes more troublesome and time-consuming. A common theme is the difficulty in locating the segments of a page in which the target information is contained, which we call the informative blocks. This article reports on the Recognising Informative Page Blocks algorithm (RIPB), which is able to identify the informative block in a web page so that information extraction algorithms can work on it more efficiently. RIPB relies on an existing algorithm for vision-based page block segmentation to analyse and partition a web page into a set of visual blocks, and then groups related blocks with similar content structures into block clusters by using a tree edit distance method. RIPB recognises the informative block cluster by using tree alignment and tree matching. A series of experiments were performed, and the conclusions were that RIPB was more than 95% accurate in recognising informative block clusters, and improved the efficiency of information extraction by 17%.
dc.formattext/html
dc.identifierhttps://doi.org/10.3217/jucs-014-11-1893
dc.identifierhttps://lib.jucs.org/article/29101/
dc.identifier.urihttps://openrepository.mephi.ru/handle/123456789/9772
dc.languageen
dc.publisherJournal of Universal Computer Science
dc.relationinfo:eu-repo/semantics/altIdentifier/eissn/0948-6968
dc.relationinfo:eu-repo/semantics/altIdentifier/pissn/0948-695X
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightsJ.UCS License
dc.sourceJUCS - Journal of Universal Computer Science 14(11): 1893-1910
dc.subjectinformation extraction
dc.subjectinformative block
dc.subjectvisual block
dc.titleRecognising Informative Web Page Blocks Using Visual Segmentation for Efficient Information Extraction
dc.typeResearch Article
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