Proceedings of the 2007 ACM Symposium on Document Engineering 2007
DOI: 10.1145/1284420.1284435
|View full text |Cite
|
Sign up to set email alerts
|

Extracting reusable document components for variable data printing

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

0
4
0

Year Published

2010
2010
2018
2018

Publication Types

Select...
2
2

Relationship

1
3

Authors

Journals

citations
Cited by 4 publications
(4 citation statements)
references
References 7 publications
0
4
0
Order By: Relevance
“…1. The folha dataset (obtained from a Brazilian newspaper's RSS feed), 4 which is comprised by a large number of text articles (mostly short) and pictures; 2. The lipsum dataset, which is smaller and contains larger, randomly generated text articles.…”
Section: Generating Test Instancesmentioning
confidence: 99%
See 1 more Smart Citation
“…1. The folha dataset (obtained from a Brazilian newspaper's RSS feed), 4 which is comprised by a large number of text articles (mostly short) and pictures; 2. The lipsum dataset, which is smaller and contains larger, randomly generated text articles.…”
Section: Generating Test Instancesmentioning
confidence: 99%
“…Systems for assembling documents are not new. Variable Data Printing (VDP) [4] systems evolved from earlier transactional businesses such as direct mail marketing, bank statements, bills and others [9], where static content is mixed with custom data (i.e. relevant client information).…”
Section: Introductionmentioning
confidence: 99%
“…The structure of a PDF document has been described many times before [3,4,5] and there is no need to go over it in detail again. A PDF is effectively a serialization of an object hierarchy.…”
Section: The Structure Of a Pdf Pagementioning
confidence: 99%
“…We have already developed a PDF parser as part of COG Extractor [5], and so were able to reuse this as part of our compiler. Internally, COG Extractor produces an abstract syntax tree from the content stream.…”
Section: Parsingmentioning
confidence: 99%