XRCE participation to the 2009 book structure task
INEX'09 Proceedings of the Focused retrieval and evaluation, and 8th international conference on Initiative for the evaluation of XML retrieval
Structure extraction from PDF-based book documents
Proceedings of the 11th annual international ACM/IEEE joint conference on Digital libraries
Challenges in generating bookmarks from TOC entries in e-books
Proceedings of the 2012 ACM symposium on Document engineering
Searching online book documents and analyzing book citations
Proceedings of the 2013 ACM symposium on Document engineering
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Table of contents (TOC) recognition has attracted a great deal of attention in recent years. After reviewing the merits and drawbacks of the existing TOC recognition methods, we have observed that book documents are multi-page documents with intrinsic local format consistency. Based on this finding we introduce an automatic TOC analysis method through clustering. This method first detects the decorative elements in TOC pages. Then it learns a layout model used in the TOC pages through clustering. Finally, it generates TOC entries and extracts their hierarchical structure under the guidance of the model. More specifically, broken lines are taken into account in the method. Experimental results show that this method achieves high accuracy and efficiency. In addition, this method has been successfully applied in a commercial E-book production software package.