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Danica Damljanovi ć University of Sheffield danica@dcs.shef.ac.uk

Usability Enhancement Methods in Natural Language Interfaces for Querying Ontologies Birmingham, 12 April, 2011. Danica Damljanovi ć University of Sheffield danica@dcs.shef.ac.uk. Outline. Background: What are Ontologies ? What are Natural Language Interfaces (NLIs)?

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Danica Damljanovi ć University of Sheffield danica@dcs.shef.ac.uk

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  1. Usability Enhancement Methods in Natural Language Interfaces for Querying OntologiesBirmingham, 12 April, 2011 DanicaDamljanović University of Sheffield danica@dcs.shef.ac.uk

  2. Outline • Background: • What are Ontologies? • What are Natural Language Interfaces (NLIs)? • What are Usability Enhancement Methods? • Objective • Improve NLIs to Ontologies with usability enhancement methods • Our approach • Two NLI systems for querying ontologies: • QuestIO • FREyA • Two usability studies to test the usability enhancement methods • Findings • Demo • Conclusion

  3. MARY <is a> PERSON UNIVERSITY OF SHEFFIELD <is an> ORGANISATION MARY <works for> UNIVERSITY OF SHEFFIELD SHEFFIELD <is a> CITY UNIVERSITY OF SHEFFIELD <is located in> SHEFFIELD UNITED KINGDOM <is a> COUNTRY SHEFFIELD <is located in> UNITED KINGDOM MARY <lives in> SHEFFIELD Mary works for University of Sheffield, which is located in Sheffield. Sheffield is located in the United Kingdom. Mary lives in Sheffield. SELECT ?country WHERE { ?person <lives in> ?city ?city <located in> ?country • FILTER ?person = MARY }

  4. In which country does Mary live?

  5. What are Usability Enhancement Methods? • Who are the users? • application developers • end users

  6. The Objective • Increase usability of Natural Language Interfaces to ontologies • For end users: increase precision and recall • For application developers: decrease the time for customisation

  7. Our Approach

  8. QuestIO 1.15 1.19 compare

  9. QuestIO prototype

  10. QuestIO: User Evaluation • Usability testing: • effectiveness: could the tasks could be finished using QuestIO • efficiency: how quickly? • user satisfaction • System Usability Scale (SUS) • subjective (was it easy to formulate a query?, etc.) • Experimental setup: • a complete counterbalanced repeated measures, task-based evaluation design • Baseline (search engines) vs. QuestIO • 12 subjects familiar with the domain (GATE software) • four tasks: • three defined, e.g. ...find parameters of Cebuano gazetteer... • one undefined task, ...find anything you want about GATE software...

  11. QuestIO User Evaluation: Results • Effectiveness: • the scale from 0 (easy) to 2 (impossible) • 0.355 for QuestIO in comparison to 0.895 for baseline, p = 0 .001 • Efficiency: • the subjects significantly slower when using baseline (157s) in comparison to QuestIO(107s), p=0.001 User satisfaction: SUS score satisfactory (69.38) • Tasks: • defined tasks: user satisfaction reaching 90% • undefined tasks: user satisfaction low (~44%)

  12. QuestIO: weaknesses • Lexical failures: Tokenizer vs. Tokeniser • Conceptual failures: • missing concepts, relations, or both • The users not being aware of why the failures happened • Can this be improved with usability enhancement methods such as feedback and clarification dialogs?

  13. FREyA - Feedback, Refinement, Extended VocabularyAggregator • Feedback: showing the user system interpretation of the query • Refinement: • resolving ambiguity: generating dialog whenever one term refers to more than one concept in the ontology (precision) • Extended Vocabulary: • expressiveness: generating dialog whenever an “unknown” term appears in the question (recall) • portability: no need for customisation from application developers • The dialog: • generated by combining the syntactic parsing and ontology-based lookup • the system learns from the user’s selections

  14. Feedback: answer is found

  15. Feedback: No answer is found

  16. Feedback: User Evaluation • Usability testing: • effectiveness • efficiency • user satisfaction • System Usability Scale (SUS) • subjective (was it easy to formulate a query?, etc.) • Experimental setup: • 30 subjects outside Sheffield, two domains (GATE software and US geography) • four tasks: • three defined: • two repeated from the previous study • one where the answer was not available, e.g. ...find states bordering hawaii... • one undefined task, ...find anything you want about GATE software or rivers, cities, ... in the United States...

  17. Does the feedback make any difference? • Effectiveness: yes , p=0.01, 0.67 for QuestIO, 0.13 for FREyA • Efficiency: no, although the overall result differs (180.5 seconds for QuestIO, 155.27 seconds for FREyA), 2-tailed independent t-test reveals that this difference is not significant (p=0.852) • Query Formulation: for the defined tasks there is no difference in the perception of the difficulty of the supported language (F=5.255, p=0.071), but for the undefined tasks the users believed that the language supported by FREyA is easier! (F=8.016, p=0.015) • Showing that the system knows about certain concepts, but cannot find any relation between them was not clear. • Interactive features were well accepted.

  18. FREyA Workflow

  19. Demo • http://gate.ac.uk/freya ESWC 2010

  20. Evaluation: correctness • Mooney GeoQuery dataset, 250 questions • 34 no dialog, 14 failed to be answered • Precision=recall=94.4%

  21. Evaluation: Learning • 10-fold cross-validation • 202 Mooney GeoQuery questions that could be correctly mapped into SPARQL and required dialog • improvement from 0.25 to 0.48 • Errors: ambiguity and sparseness

  22. Evaluation: Ranking Mean Reciprocal Rank: 0.76

  23. Learning the Correct Ranking • Randomly selected 103 dialogs from 202 questions (343 dialogs) • MRR increased for 6% from 0.72 to 0.78

  24. Evaluation: Answer Type

  25. Conclusion • Combining syntactic parsing with ontology-based lookup in an interactive process of feedback and query refinement can increase the precision and recall of NLIs to ontologies, • while reducing the time for customisation by shifting some tasksfrom application developers to end users.

  26. Thank You! email: danica@dcs.shef.ac.uk

  27. More information... • D. Damljanovic, M. Agatonovic, H. Cunningham: FREyA: an Interactive Way of Querying Linked Data, 1st Workshop on Question-Answering over Linked Data, in conjunction with ESWC’11, 2011. (to appear) • D. Damljanovic, M. Agatonovic, H. Cunningham: Natural Language Interfaces to Ontologies: Combining Syntactic Analysis and Ontology-based Lookup through the User Interaction. In Proceedings of the 7th Extended Semantic Web Conference (ESWC 2010), Springer Verlag, Heraklion, Greece, May 31-June 3, 2010. PDF • D. Damljanovic, M. Agatonovic, H. Cunningham: Identification of the Question Focus: Combining Syntactic Analysis and Ontology-based Lookup through the User Interaction. In Proceedings of the 7th Language Resources and Evaluation Conference (LREC 2010), ELRA 2010, La Valletta, Malta, May 17-23, 2010. PDFD. Damljanovic. Towards portable controlled natural languages for querying ontologies. In Rosner, M., Fuchs, N., eds.: Proceedings of the 2nd Workshop on Controlled Natural Language. Lecture Notes in Computer Science. Springer Berlin/Heidelberg, Marettimo Island, Sicily (September 2010)

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