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Learning Structure and Schemas from Documents

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Cover of 'Learning Structure and Schemas from Documents'

Table of Contents

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    Book Overview
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    Chapter 1 Learning Structure and Schemas from Heterogeneous Domains in Networked Systems Surveyed
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    Chapter 2 Handling Hierarchically Structured Resources Addressing Interoperability Issues in Digital Libraries
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    Chapter 3 Administrative Document Analysis and Structure
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    Chapter 4 Automatic Document Layout Analysis through Relational Machine Learning
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    Chapter 5 Dataspaces: Where Structure and Schema Meet
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    Chapter 6 Transductive Learning of Logical Structures from Document Images
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    Chapter 7 Progressive Filtering on the Web: The Press Reviews Case Study
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    Chapter 8 A Hybrid Binarization Technique for Document Images
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    Chapter 9 Digital Libraries and Document Image Retrieval Techniques: A Survey
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    Chapter 10 Mining Biomedical Text towards Building a Quantitative Food-Disease-Gene Network
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    Chapter 11 Mining Tinnitus Data Based on Clustering and New Temporal Features
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    Chapter 12 DTW-GO Based Microarray Time Series Data Analysis for Gene-Gene Regulation Prediction
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    Chapter 13 Integrating Content and Structure into a Comprehensive Framework for XML Document Similarity Represented in 3D Space
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    Chapter 14 Modelling User Behaviour on Page Content and Layout in Recommender Systems
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    Chapter 15 MANENT: An Infrastructure for Integrating, Structuring and Searching Digital Libraries
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    Chapter 16 Low-Level Document Image Analysis and Description: From Appearance to Structure
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    Chapter 17 Model Learning from Published Aggregated Data
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    Chapter 18 Data De-duplication: A Review
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    Chapter 19 A Survey on Integrating Data in Bioinformatics
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mendeley
37 Mendeley
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Title
Learning Structure and Schemas from Documents
Published by
Springer Science & Business Media, September 2011
DOI 10.1007/978-3-642-22913-8
ISBNs
978-3-64-222912-1, 978-3-64-222913-8
Editors

Biba, Marenglen, Xhafa, Fatos

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Portugal 1 3%
Netherlands 1 3%
Ireland 1 3%
Italy 1 3%
Brazil 1 3%
Mexico 1 3%
Unknown 31 84%

Demographic breakdown

Readers by professional status Count As %
Student > Master 9 24%
Student > Bachelor 7 19%
Researcher 6 16%
Student > Ph. D. Student 6 16%
Professor 3 8%
Other 6 16%
Readers by discipline Count As %
Computer Science 24 65%
Business, Management and Accounting 3 8%
Engineering 3 8%
Environmental Science 2 5%
Linguistics 1 3%
Other 4 11%