Automatically Annotating Structured Web Data Using a SVM-Based Multiclass Classifier

Daiyue Weng, Jun Hong, David A. Bell

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)


In this paper, we propose a new learning approach to Web data annotation, where a support vector machine-based multiclass classifier is trained to assign labels to data items. For data record extraction, a data section re-segmentation algorithm based on visual and content features is introduced to improve the performance of Web data record extraction. We have implemented the proposed approach and tested it with a large set of Web query result pages in different domains. Our experimental results show that our proposed approach is highly effective and efficient.
Original languageEnglish
Title of host publicationWeb Information Systems Engineering - WISE 2014: 15th International Conference, Thessaloniki, Greece, October 12-14, 2014, Proceedings, Part I
Pages115 - 124
Number of pages10
ISBN (Electronic)9783319117492
ISBN (Print)9783319117485
Publication statusPublished - 2014

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743


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