Augmented Hyperbooks through Conceptual Integration

1. Augmented Hyperbooksthrough Conceptual Integration G. Falquet L. Nerima J.-C. Ziswiler Information System Interfaces – University of Geneva cui.unige.ch/isi

2. interface = generated hyperdocuments Context: Hyperbook model Virtual document model domain ontology interface specification information fragments FNZ - Augmented Hyperbooks

3. O O O O F F F F Context: Library of Hyperbooks • Augmented reading in a digital library • Enrich one hyperbook with contents coming from others HT+ HT FNZ - Augmented Hyperbooks

4. Augmentation through Ontology Alignment 1. Align the book ontologies • compute concept similarities sij O similarity links F FNZ - Augmented Hyperbooks

5. Augmentation through Ontology Alignment 2. Use similarity links to infer hypertext links similarity link O HT+ HT F O F FNZ - Augmented Hyperbooks

6. 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 …" FNZ - Augmented Hyperbooks

7. This study • Alignment method that works with less formalized (incomplete) ontology • Test on two "realistic" hyperbooks Sources • Multifunctional agriculture site • World Trade Organization (WTO) FNZ - Augmented Hyperbooks

8. The Hyperbooks WTO partial ontology "domestic support" "1-hour" ontology page extracts from WTO site Multifunctional agriculture web site FNZ - Augmented Hyperbooks

9. 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 FNZ - Augmented Hyperbooks

10. Similarity measure 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) FNZ - Augmented Hyperbooks

11. Sample similarity values Word matching alone is not sufficient • same words used for different concepts FNZ - Augmented Hyperbooks

12. Similarity link creation Create link if FM > FMt and WM > WMt For the test hyperbooks : WMt = FMt = 0 FM SIM(a, {b1, …, bn}) FMt WM WMt FNZ - Augmented Hyperbooks

13. 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) FNZ - Augmented Hyperbooks

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17. 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 FNZ - Augmented Hyperbooks