Most recognition work has focused on recognizing logical structure from document layout. Significant research has been carried out in the context of OCR-based document recognition systems. For a complete up-to-date bibliography on work in this area, we refer the reader to the online bibliography on document understanding available at FTP://dimund.umd.edu/pub/DOCBIB/databases/DocumentBib.bib. The site also provides a searching tool using the Internet Gopher.
See [PR92] for details on recognizing logical structure from the layout information present in a Postscript file. This is a difficult problem and re-emphasizes the earlier comment on PDF and the shortcomings in storing electronic documents in a purely layout-oriented form.
Relatively little work has been done in recognizing document structure from electronic markup. The work on Chamelion [MOB90] and related work in the area of attribute grammars [Yel88] could be used to extract logical structure from electronic documents. Tools such as the Cornell Synthesizer Generator [RT88b][RT88a][RT84] and the Centaur system [Bor88] can also be used to build such recognizers. The key to building such recognizers successfully is the robustness and applicability of the high-level models used. For details on other attempts at recognizing structure from markup, see [Arn92][AW91][AM91][Arn91].