falcon-ao: results for oaei 2007

Falcon-AO: Results for OAEI 2007

Wei Hu, Yuanyuan Zhao, Dan Li Gong Cheng, Honghan Wu, and Yuzhong Qu

School of Computer Science and Engineering, Southeast University, Nanjing 210096, China

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Outline

Overview Features and Capabilities OAEI 2007 Results Conclusion

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Overview of Falcon-AO

Falcon-AO is an automatic ontology matching system to help establish interoperability between (Semantic) Web applications using different while related ontologies. Matching Web ontologies described in RDF(S) and OWL Implemented in Java An open source project under the Apache 2.0 license http://iws.seu.edu.cn/projects/matching/

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History of Falcon-AO – v0.3 (2005)

2005

Linguistic Matching + Graph Matching

LMO + GMO

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History of Falcon-AO – v0.6 (2006)

2005

Linguistic Matching + Graph Matching + Partition-based

V-Doc + GMO + I-Sub + PBM

2006

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History of Falcon-AO – v0.7 (2007)

Linguistic Matching + Graph Matching + Partition-based

V-Doc + GMO + I-Sub + PBM

2006

2005

2007

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What’s New in Falcon-AO v0.7

Bug repair Optimization Open source

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Architecture

Model Pool

• Parsing ontologies into in-memory models using Jena

• Adjusting models using coordination rules

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Architecture (cont’d.)

Matcher Library

• V-Doc, I-Sub: two light- weighted linguistic matchers

• GMO: an iterative structural matcher

• PBM: partition-based block matching of large ontologies

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Architecture (cont’d.)

Alignment Set

• Generating alignments using a widely-accepted RDF/XML format

• Evaluating generated alignments against reference alignments

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Architecture (cont’d.)

Central Controller

• Configuring matching strategies

• Executing matchers

• Combining similarity in terms of the measures of the linguistic and structural comparability

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Architecture (cont’d.)

Repository

• Storing useful data during the matching process

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Outline

Overview Features and Capabilities OAEI 2007 Results Conclusion

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Features and Capabilities – V-Doc

V-Doc – constructing virtual documents for ontology matching A light-weighted linguistic matcher The virtual document of a domain entity in an ontology contains:

its local description, such as labels or comments its neighboring information

Document similarity is calculated via the TF/IDF technique.

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Features and Capabilities – GMO

GMO – graph matching for ontologies An iterative structural matcher Using RDF bipartite graphs to represent ontologies Computing structural similarity between domain entities and between

statements in ontologies by recursively propagating similarity in the bipartite graphs

Ontologies + external mappings GMO additional mappings

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Features and Capabilities – PBM

PBM – partition-based block matching of large-scale ontologies Based on the divide-and-conquer idea

Advantages: Avoiding OUT-OF-MEMORY Decreasing the runtime

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Features and Capabilities – Coordination Rules

Heterogeneous ways in expressing ontologies Falcon-AO implements 21 coordination rules to eliminate “useless” axi

oms and reduce structural heterogeneity. Removing redundant and worthless statements

owl:imports Complementing statements

owl:inverseOf Reconstructing the RDF List structure

Replacing RDF collection vocabularies (rdf:first …) with rdfs:member

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Features and Capabilities – Similarity Combination

Falcon-AO develops an approach to automatically tune the thresholds of different matchers based on the measures of The linguistic comparability:

#mappings found by I-Sub / min (#domain entities in two ontologies) The structural comparability (confidence):

#mappings found by GMO / #mappings found by I-Sub or V-Doc

General scheme Higher comparability, lower cutoff Unmatchable if both lower

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Outline

Presentation of the system Features and capabilities OAEI 2007 Results Conclusion

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Towards a Generic Practical Tool

Benchmark 5 min for all

Directory 2 min for all 4,639 tasks

Food 5.75 h

EnvironmentGEMET vs. AGROVOC 33 min

GEMET vs. NALT 1.2 h

Library 40 min

Conference 3 min for all 91 tasks

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Outline

Presentation of the system Features and capabilities OAEI 2007 Results Conclusion

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Conclusion

Falcon-AO (v0.7) performs well on most of matching tasks.

In the near future, we are looking forward to extending Falcon-AO to: Integrating new matchers, especially instance-based approaches Discovering mappings between ontologies and RDB schemas Supporting data transformation by deriving executable mappings from

schema matching

Thanks for your attention!

Any comments are welcome!

Welcome to Beijing 2008!