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SIM-DL Towards a Semantic Similarity Measurement Theory for the Description Logic ALCNR in Geographic Information Retrie

SIM-DL Towards a Semantic Similarity Measurement Theory for the Description Logic ALCNR in Geographic Information Retrieval Krzysztof Janowicz Institute for Geoinformatics; University of Münster. Outline. Motivation: Yet Another Similarity Theory? Similarity & Subsumption based IR

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SIM-DL Towards a Semantic Similarity Measurement Theory for the Description Logic ALCNR in Geographic Information Retrie

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  1. SIM-DL • Towards a Semantic Similarity Measurement Theory for the Description Logic ALCNR in Geographic Information Retrieval • Krzysztof Janowicz • Institute for Geoinformatics; University of Münster Krzysztof Janowicz

  2. Outline • Motivation: Yet Another Similarity Theory? • Similarity & Subsumption based IR • Matching Scenario • SIM-DL Framework • Human Subject Testing • Results, Conclusions & Outlook SIM-DL (for ALCNR)

  3. Yet Another Similarity Theory? Measured between (re)representation! Available theories Available ontologies (DL!) http://flickr.com/photos/genista/25390358/ SIM-DL (for ALCNR)

  4. Similarity & Subsumption based Retrieval SIM-DL (for ALCNR)

  5. Similarity vs. Subsumption • Subsumption-based Retrieval (+) Results fit user’s requirements (subconcepts!) (-) Too generic / too specific result set (-) Artificial search concept • Similarity-based Retrieval (+) Search concept = searched concept (-) Results not necessarilyfit user’s requirements SIM-DL (for ALCNR)

  6. Matching-Scenario • Accommodation web portal • External services (SOA) • Use shared base vocabulary • Local interface and terminology • Hotel, Houseboat, Youth Hostel, Botel,…. Task: Integrate Amsterdam-Accommodation Service Where to put botels? SIM-DL (for ALCNR)

  7. Houseboats, Hotel &Botel SIM-DL (for ALCNR)

  8. Some Impressions SIM-DL (for ALCNR) Pictures received by email, taken from wikipedia and http://www.hotels.nl/amsterdam/botel/

  9. SIM-DL: Representation (ALCNR) SIM-DL (for ALCNR)

  10. SIM-DL: Framework • Specify search concept and context • Rephrase concepts to canonical NF • Generate alignment matrix • Apply sim-functions for selected combinations • Derive normalized overall similarity SIM-DL (for ALCNR)

  11. Clcs ≡ Housing Cs ≡ Botel SIM-DL: Search Concept & Context (-) Results not necessarilyfit user’s requirements  Define Context SIM-DL (for ALCNR)

  12. Rephrase Concepts to Canonical NF • ALCNR Normal Form: + Rewriting rules (e.g. R() ≡ (≤ 0 R)) + Minimal set of descriptions (concepts)  Canonical Normal Form SIM-DL (for ALCNR)

  13. Generate Alignment Matrix • Cartesian Product Cs Ct Hierarchies Neighborhoods Co-Occurrence H > N > CO SIM-DL (for ALCNR)

  14. max_distance edge_distance Apply Similarity-Functions (for selected combinations) • Individual similarity functions for each DL language constructor: {union, intersection, role-intersection, existential quantification, value restriction, cardinality} • For Hierarchies, Neighborhoods, Co-Occurrence SIM-DL (for ALCNR)

  15. Amalgamated & Normalized Overall Similarity • Union-Constructor: • Weighted sum of similarities on CNF union level • Weightings derived from A-Box, T-Box or A&T-Box • Intersection-Constructor: • Sum of similarities on CNF intersection level • Normalization to [0,1] SIM-DL (for ALCNR)

  16. Human Subject Testing: Roles & Fillers User input Auto. weighted average (>) Multiplicative approach (<) Disjoint from watercourse Meets river SIM-DL (for ALCNR)

  17. Near ? Results, Conclusion & Outlook • SIM-DL combines subsumption and similarity • Adapts results from psychology & computer science  Cognitive Engineering ;-) • Only basic model of Alignment and Context • More Human Subject Tests needed • More expressive DL • Usability? SIM-DL (for ALCNR)

  18. Questions? Thanks for your attention! Visit www.similarity-blog.de for related literature. From: http://www.jobblog.ch/sommer-250 Krzysztof Janowicz

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