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© Paul Buitelaar – November 2007, Busan, South-Korea Evaluating Ontology Search Towards Benchmarking in Ontology Search Paul Buitelaar, Thomas.

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Presentation on theme: "© Paul Buitelaar – November 2007, Busan, South-Korea Evaluating Ontology Search Towards Benchmarking in Ontology Search Paul Buitelaar, Thomas."— Presentation transcript:

1 © Paul Buitelaar – EON@ISWC07, November 2007, Busan, South-Korea Evaluating Ontology Search Towards Benchmarking in Ontology Search Paul Buitelaar, Thomas Eigner Competence Center Semantic Web & Language Technology Lab DFKI GmbH Saarbrücken, Germany

2 © Paul Buitelaar – EON@ISWC07, November 2007, Busan, South-Korea Overview Ontology Search  Knowledge reuse (integration with Ontology Learning) OntoSelect  Browse (ontologies, labels, classes, properties)  Search by topic Evaluating Ontology Search  Benchmark (evaluation) data set  Experiment (compare SWOOGLE, OntoSelect) Conclusions

3 © Paul Buitelaar – EON@ISWC07, November 2007, Busan, South-Korea Ontology Search There are more and more ontologies published on the (Semantic) Web  Available as RDFS or OWL files (also still DAML) Opens up possibilities for reuse of knowledge  Access through ontology search engines and/or (manual/automatic) organization in ontology libraries But: increasingly harder to find the right one for your application  Increasing research in ontology search/selection (Alani et al., Buitelaar et al., Ding et al., Sabou et al.) – SWOOGLE, OntoSelect, Watson

4 © Paul Buitelaar – EON@ISWC07, November 2007, Busan, South-Korea OntoSelect Ontology Library and Search Engine http://olp.dfki.de/OntoSelect  Monitors the web for ontologies with automatic harvesting and indexing  Browse and search On ontologies, classes, properties and (multilingual) labels Ontology search integrates relevance feedback over Wikipedia for search term  Ontology publishing Submit ontologies - will be automatically integrated  Statistics On formats, languages, labels used, ontology publishing Paul Buitelaar, Thomas Eigner, Thierry Declerck OntoSelect: A Dynamic Ontology Library with Support for Ontology Selection In: Proc. of the Demo Session at the International Semantic Web Conference, Hiroshima, Japan, Nov. 2004.

5 © Paul Buitelaar – EON@ISWC07, November 2007, Busan, South-Korea OntoSelect – Browse

6 © Paul Buitelaar – EON@ISWC07, November 2007, Busan, South-Korea Ontology Search

7 © Paul Buitelaar – EON@ISWC07, November 2007, Busan, South-Korea Keyword as Wikipedia Topic

8 © Paul Buitelaar – EON@ISWC07, November 2007, Busan, South-Korea Keyword Expansion (Extraction) Relevance Feedback from Wikipedia

9 © Paul Buitelaar – EON@ISWC07, November 2007, Busan, South-Korea Ranked Results (Browsable)

10 © Paul Buitelaar – EON@ISWC07, November 2007, Busan, South-Korea Search Criteria Relevance criteria address ontology content, structure, status:  Coverage - Term Matching How many of the terms in a text collection are covered by labels for classes and properties?  Structure - Properties Relative to Classes How detailed is the knowledge structure that the ontology represents?  Connectedness - Number of Included Ontologies Is the ontology connected to other ontologies and how well established are these?

11 © Paul Buitelaar – EON@ISWC07, November 2007, Busan, South-Korea Evaluation – Benchmark Benchmark: 15 Wikipedia topics and 57 manually assigned ontologies out of 1056 cached through OntoSelect 15 Wikipedia topics were selected out of the set of all (37284) class/property labels in OntoSelect, by:  Filtering out labels that did not correspond to a Wikipedia page > 5658 labels / topics  5658 labels were used as search terms in SWOOGLE to filter out labels that returned less than 10 ontologies (out of the 1056 in OntoSelect) > 3084 labels / topics  Out of 3084 labels we manually selected useful topics, e.g. we left out very short labels (‘v’) and very abstract ones (‘thing’) > 50 topics  We randomly selected 15 for which we manually checked the ontologies retrieved from OntoSelect and SWOOGLE > 15 topics with 57 assigned ontologies

12 © Paul Buitelaar – EON@ISWC07, November 2007, Busan, South-Korea Evaluation – Benchmark by Topic 15 (Wikipedia) topics with number of assigned ontologies:  Atmosphere (2)  Biology (11)  City (3) http://www.mindswap.org/2003/owl/geo/geoFeatures.owl http://www.glue.umd.edu/ katyn/CMSC828y/location.daml http://www.daml.org/2001/02/geofile/geofile-ont  Communication (10)  Economy (1)  Infrastructure (2)  Institution (1)  Math (3)  Military (5)  Newspaper (2)  Oil (0)  Production (1)  Publication (6)  Railroad (1)  Tourism (9)

13 © Paul Buitelaar – EON@ISWC07, November 2007, Busan, South-Korea Evaluation – Experiment Comparison of (average) results between SWOOGLE and OntoSelect Use OntoSelect benchmark  15 topics (queries)  57 assigned ontologies (relevance assessments)  1056 ontologies (data set) Use different configurations for OntoSelect  With/without keyword expansion/extraction  With/without class names (in addition to labels)  With/without property labels  Weighting of relevance criteria  …

14 © Paul Buitelaar – EON@ISWC07, November 2007, Busan, South-Korea Evaluation – Results

15 © Paul Buitelaar – EON@ISWC07, November 2007, Busan, South-Korea Evaluation – Weighting of ‚title‘

16 © Paul Buitelaar – EON@ISWC07, November 2007, Busan, South-Korea Conclusions Conclusions on evaluation are too early  Many more configurations (weights) to compare  Extend the benchmark  Comparison with other ontology search engines Main contribution of the presented work  First comprehensive benchmark for topic-driven evaluation of ontology search  (Extended) Benchmark will be made publicly available http://olp.dfki.de/OntoSelect


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