1. 1 A Tool to Support Ontology Creation Based on Incremental Mini-ontology Merging Zonghui Lian

2. 2 Introduction Ontology-based information extraction  Robust to change  Multi-slot filling  Source-independent  Drawback: ontology has to be generated manually Tango (Table ANalysis for Generating Ontologies) An information gathering engine that infers the unknown objects and relations in a known context into ontologies automatically

3. 3 TANGO

4. 4 Source table understanding Constraints discovery Concept matching Ontology merging Domain ontology adjusting

5. 5 The Flow of Ontology Integration Ontology mappingKB conflict checkingMake suggestion Data storage Ontology Merging Mini-ontology User’s interactions

6. 6 Research Issues Name conflict detection Union/selection detection and merging Composition/decomposition detection and merging Constraint conflict detection Relationship set conflict detection New concept detection and merging Ontology consistency checking after integration

7. 7 Name Conflict Detection

8. 8 Union/Selection Detection & Merging Graduate Student is a subset of Student

9. 9 Composition/Decomposition Detection & Merging Name = First Name + Last Name

10. 10 Constraint Conflict Detection

11. 11 Constraint Conflict Detection

12. 12 Relationship Set Conflict Detection ?

13. 13 Relationship Set Conflict Detection

14. 14 Other Issues New concept detection and merging Ontology consistency checking after mapping

15. 15 Ontology Mapping Based on mapping technique introduced in EXD04 Need to make improvement and change according to the requirements of ontology mapping

16. 16 Ontology Mapping Data-value characteristics detection  Schema mapping: data values in tables  Ontology mapping: dictionaries & data values in a set of source tables Reference ontology inference  Schema mapping: reference ontology  Ontology mapping: data frame library (option)

17. 17 Ontology Mapping New concept detection  Schema mapping: none  Ontology mapping: mark unmatched attributes

18. 18 Ontology Mapping Relationship set mapping  Schema mapping: none  Ontology mapping

19. 19 Ontology Mapping Person|Student has Name Graduate Student has Name

20. 20 Ontology Mapping ? Phone Extension

21. 21 Ontology Mapping Detailed mapping information detection  Schema mapping: need to be improved  Ontology mapping: Base on values to detect subset/superset and merge/split Human experts refine interactively

22. 22 Ontology Merging Name conflict  Based on growing ontology Union/selection merging  Generalization/specialization

23. 23 Graduate Student is a subset of Student

24. 24 Ontology Merging Composition/decomposition merging  Aggregation

25. 25 Name = First Name + Last Name

26. 26 Ontology Merging Relationship set merging  Map w/out conflicts: merge  Map with conflict(s): Fake conflicts: resolve the conflict Real conflicts: Add new relationship set(s) or change the current one

27. 27 Evaluation Users A package (more than just software) Users’ report Analysis  Precision

28. 28 Contributions Can extend DEG's ontology-based data extraction system with a set of ontology growing features Can contribute to generate a domain- specific ontology with minimal human intervention