Augmented Hyperbooksthrough Conceptual Integration

G. Falquet

L. Nerima

J.-C. Ziswiler

Information System Interfaces – University of Geneva

cui.unige.ch/isi

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Context: Hyperbook model

domain ontology

information fragments

interface=

generated hyperdocuments

interfacespecification

Virtual document model

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F

O

F

O

F

O

F

O

HT

HT+

Context: Library of Hyperbooks

• Augmented reading in a digital library

• Enrich one hyperbook with contents coming from others

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Augmentation through Ontology Alignment

1. Align the book ontologies– compute concept similarities

F

O

similaritylinks

sij

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Augmentation through Ontology Alignment

2. Use similarity links to infer hypertext links

F

OF

O

HT

HT+similaritylink

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Problem

Ontology alignment algorithms need well structured ontologies

BUT– Hyperbook writers are not knowledge engineers

– HT’04 reviewer"... nice approach … doubts about feasibility … " 

– C. Marshall, F. Shipman. Which semantic web ? "The difficulty of knowledge acquisition, representation and

reasonsing has a long history of being underestimated …"

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This study

• Alignment method that works with less formalized (incomplete) ontology

• Test on two "realistic" hyperbooks

Sources

– Multifunctional agriculture

site

– World Trade Organization

(WTO)

QuickTime™ et undécompresseur TIFF (LZW)

sont requis pour visionner cette image.

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The Hyperbooks

"1-hour" ontology

page extracts fromWTO site

WTO partial ontology"domestic support"

Multifunctional agricultureweb site

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Alignment technique

• Adapted from [Rodriguez & Egenhofer] concept comparison method

• Word Matching– compare the words in the terms

"agricultural training service" <--> "agricultural landscape"

– stop word filtering– synonym resolution

• Fragment matching (feature matching)– compare the fragments connected to both concepts

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Compare the sets of words

| A B |

| A B | + | A – B | + (1 - ) | B – A |

depends on the relative depths of a and b in the concept hierarchy

min { depth(a), depth(b) }

depth(a) + depth(b)

Similarity measure

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Source concept Target concept WM FMfood security public stockholding programmes for food security 0.416667 0.596379Norwegian agriculture Domestic support in agriculture 0.375 0.266805agricultural landscape agricultural training services 0.375 0food security domestic food aid 0.37037 0.520896Multifunctional agriculture Domestic support in agriculture 0.357143Agricultural production agricultural training services 0.294118 0Agricultural production domestic food aid 0.290323 0.0413793cultural heritage and environmental benefits research in environmental programmes 0.25cultural heritage and environmental benefits payments for environmental and regional assistance 0.185185 0.237037Agricultural production public stockholding programmes for food security 0.173077 0.111901high standards (plants, animal, public health) public stockholding programmes for food security 0.166667high standards (plants, animal, public health) inspection of particular products 0.149425food security Domestic support in agriculture 0 0.593243food security Resource retirement programmes 0 0.46801Non-trade concerns (NTCs) Domestic support in agriculture 0 0.463183food security Amber box 0 0.388739

Sample similarity values

Word matching alone is not sufficient– same words used for different concepts

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Similarity link creation

Create link if FM > FMt and WM > WMt

For the test hyperbooks : WMt = FMt = 0

FM

WM

SIM(a, {b1, …, bn})

WMt

FMt

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Reading the Augmented Hyperbook

Generate interface documents and links

– original contents (fragments)

– inferred links to relevant concepts & contents

– inferred transclusion and expand-in-place (stretch text)

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Conclusion

Alignment technique for "light" ontologies – augment hyperbooks written by non knowledge engineers– read hyperbooks "in a context"

Further experiments (Oct. 2005)– e-learning: integrate/augment hyperbooks written by students– collection of hyperized scientific papers (in physics)

Perspectives– characterization of other alignment algorithms / ontologies– hyperbook interface design: usability testing