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STARLab Research Meeting July 7, 2006 Relevance Computation

STARLab Research Meeting July 7, 2006 Relevance Computation. Aldo de Moor ademoor@vub.ac.be. Relevance computation. Usefulness of definitions, efficiency of ontology engineering process very important

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STARLab Research Meeting July 7, 2006 Relevance Computation

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  1. STARLab Research Meeting July 7, 2006Relevance Computation Aldo de Moor ademoor@vub.ac.be

  2. Relevance computation • Usefulness of definitions, efficiency of ontology engineering process very important • Key problem: how to assess continuously shifting relevance of evolving common definitions? • Essential to ensure scalability • Example: how to select relevant organizational specializations?

  3. Org Ontologies (dOi + CTHOi) T > Product > Beklede_Bakvorm Kwaliteit > Geen_Luchtbellen Gelijke_Dikte

  4. Interorganizational Ont Eng v_1 v_m IOO IOO UCO UCO LCO LCO OO-1 OO-n OO-1 OO-n

  5. A Selection Procedure (1) • Pre-condition: all org. ontologies updated • Post-condition: ready to start IOO_v+1 • Core domain expert defines set of relevance definitions DR = {dr1, ...}, e.g.:

  6. A Selection Procedure (2) • Each dr  DR is used to create set of relevance relations RR, e.g.:

  7. A Selection Procedure (3) • For each org. ontology OOi • For each org. spec. dOi  OOi, calculate relevance score sr by projecting all relevance relations into the definition: • (Using the organizational concept type hierarchy CTHOi) • Sr(dOi) = 0. • For each rr RR: if :rr→ dOi, then Sr(dOi) := Sr(dOi) + 1 • Select most relevant org. spec. using this relevance score • x highest-ranked specializations (overall, by organization) • Those specializations meeting particular threshold. • Further, scalable contextualization: use lexonized relevance relations to select relevant resources from lexon / commitments-base

  8. Lexonizing Relevance Relations (NBC CTH) T > Product > Beklede_Bakvorm Kwaliteit > Geen_Luchtbellen Gelijke_Dikte ...

  9. Discussion • Relevance computation helps scale interorganizational ontology engineering • Relevance relation: in between full-graph and concept matching level (e.g. crawler Felix). When to apply which type of technique? • Only heuristic: human evaluation still very much needed. When? What? How? • Relevance relations = sets of lexons • ground CGs (larger patterns) in real-world semantics (lexons) • do a wide, lexon-driven scan of ontological resources • How to use ORM constraints to further tailor relevance computation?

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