From Legacy Documents to XML: A Conversion Framework

Chanod, Jean-Pierre; Chidlovskii, Boris; Dejean, Hervé; Fambon, Olivier; Fuselier, Jérôme; Jacquin, Thierry; Meunier, Jean-Luc

doi:10.1007/11551362_9

Cited by 10 publications

(8 citation statements)

References 4 publications

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“…Several investigators have previously identified the hierarchical tree as the appropriate logical model for tables of contents [4,6,5], especially in regard to the goal of mapping to XML output. Here, instead of propelling directly to one or another parsing algorithm, we expand on the functional roles comprising such a tree, and their mappings to layout and attribute cues.…”

Section: A Logical Representation Schemementioning

confidence: 99%

“…For example, parsing TOCs of published material provides useful cross-linking of content headings and content location during paper to digital conversion. Some approaches exploit this constraint by devising TOC parsing algorithms based on matching items in the TOC with chapter and section headings in the body of the book or article [5,6,8].…”

Section: Introductionmentioning

confidence: 99%

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On the Reading of Tables of Contents

Sarkar

Saund

2008

2008 the Eighth IAPR International Workshop on Document Analysis Systems

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This paper presents a framework for understanding tables of contents (TOC) of books, journals, and magazines. We propose a universal logical structure representation in terms of a hierarchy of entries, each of which may contain a descriptor and a locator. We enumerate graphical and perceptual cues that provide cues to parsing of tables of contents in terms of this formalism. We make initial suggestions about the form of evaluation metrics for comparing groundtruthed tables of contents with the output of recognition algorithms. Typical and atypical tables of contents are used throughout to illustrate significant phenomena that must be dealt with in principled ways in any general TOC interpretation scheme. Finally we discuss implications of our observations on the design of recognition algorithms.

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Section: A Logical Representation Schemementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

On the Reading of Tables of Contents

Sarkar

Saund

2008

2008 the Eighth IAPR International Workshop on Document Analysis Systems

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“…ALDAI offers an extended mechanism for the feature definition and management. By default, it offers a basic set of features extracted from layout-oriented documents [1]. In addition, it offers a high level script language in which to define new features or to customize existing features.…”

Section: Active Learning Componentmentioning

confidence: 99%

“…At Xerox Research Centre Europe, we are undertaking the Legacy Document Conversion project [1] which is aimed at automating different subtasks of mass document conversion to XML. The project Copyright is held by the author/owner.…”

Section: Introductionmentioning

confidence: 99%

Aldai

Chidlovskii

Fuselier

Lecerf

2006

Proceedings of the 2006 ACM Symposium on Document Engineering

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In the framework of the LegDoC project at XRCE, we present a document annotation interface with an integrated active learning component. The interface is designed to automate the semantic annotation of layout-oriented documents. We describe principal functions of this interface; we pay a particular attention to the learning component, including the feature management and different strategies of deploying the active learner in the document annotation.

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“…To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. At Xerox Research Centre Europe, we are undertaking the Legacy Document Conversion (LegDoC) project [2] which is aimed at automating different subtasks of overall mass document conversion to XML. A typical conversion task starts with a large collection of documents in PDF or HTML.…”

Section: Introductionmentioning

confidence: 99%

Document annotation by active learning techniques

Lecerf

Chidlovskii

2006

Proceedings of the 2006 ACM Symposium on Document Engineering

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We present a system for the semantic annotation of layout-oriented documents, with an integrated learning component. We introduce probabilistic learning methods on tree-like documents and we present different active learning techniques for training document annotation models. We report some preliminary results of deploying such active learning techniques on an important case of document collection annotation.

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From Legacy Documents to XML: A Conversion Framework

Cited by 10 publications

References 4 publications

On the Reading of Tables of Contents

On the Reading of Tables of Contents

Aldai

Document annotation by active learning techniques

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