Explanation Capabilities of the Open Source Case-Based Reasoning Tool myCBR

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    Explanation Capabilities of the Open Source Case-Based Reasoning Tool myCBR - Presentation Transcript

    1. CAMBRIDGE, UK, 9 DEC 2008 Explanation Capabilities of the Open Source Case-Based Reasoning Tool myCBR Thomas Roth-Berghofer Senior researcher, trb@dfki.de German Research Centre for Artificial Intelligence DFKI GmbH Samstag, 18. Juli 2009
    2. Basic explanation scenario Samstag, 18. Juli 2009
    3. „TRUST ME. I KNOW WHAT I AM DOING!“ SLEDGE HAMMER Samstag, 18. Juli 2009
    4. „TRUST ME. I KNOW WHAT I AM DOING!“ SLEDGE HAMMER Samstag, 18. Juli 2009
    5. What are explanations? Samstag, 18. Juli 2009
    6. What are explanations? Samstag, 18. Juli 2009
    7. What are explanations? Explanations are answers to questions. Samstag, 18. Juli 2009
    8. • Plug-in for popular ontology editor Protégé (Version 3.x) • Extensions provided by myCBR (Version 2.6.1): • Easy import of raw data (csv-files) • GUIs for modelling knowledge-intensive similarity measures • Similarity-based retrieval functionality • Export of domain model and similarity measures in XML format • Stand-alone retrieval engine for separate use or integration with other systems • Built-in explanation capabilities MORE INFORMATION AND DOWNLOAD: HTTP://MYCBR-PROJECT.NET Samstag, 18. Juli 2009
    9. Example domain: Used Cars Samstag, 18. Juli 2009
    10. Example domain: Used Cars Body Model Color Mileage Manufacturer Samstag, 18. Juli 2009
    11. Samstag, 18. Juli 2009
    12. Samstag, 18. Juli 2009
    13. Samstag, 18. Juli 2009
    14. Local similarity measure VISUAL FEEDBACK: COLOURING OF SIMILARITY VALUES Samstag, 18. Juli 2009
    15. Global similarity measure • Feature match: local similarity measures • Class similarity: aggregate local similarities • Weighted sum • Maximum • Minimum • Euclidian distance Samstag, 18. Juli 2009
    16. Global similarity measure • Feature match: local similarity measures • Class similarity: aggregate local similarities • Weighted sum • Maximum • Minimum • Euclidian distance Samstag, 18. Juli 2009
    17. Important attributes Samstag, 18. Juli 2009
    18. Important attributes Samstag, 18. Juli 2009
    19. Important attributes Samstag, 18. Juli 2009
    20. Searching for a car Samstag, 18. Juli 2009
    21. Searching for a car Samstag, 18. Juli 2009
    22. Searching for a car Samstag, 18. Juli 2009
    23. Searching for a car Samstag, 18. Juli 2009
    24. Searching for a car Samstag, 18. Juli 2009
    25. Questions • about domain concepts • about retrieval results • during modelling and maintenance Samstag, 18. Juli 2009
    26. Question about domain concepts • What is meant by this concept? Samstag, 18. Juli 2009
    27. Conceptual Explanations • The goal of conceptual explanations is to build links between unknown and known concepts. • Variations: • Definition: “What is a bicycle?” – “A bicycle is a land vehicle with two wheels in line. Bicycles are a form of human powered vehicle.” • Theoretical proposition: “What is force?” – “Force is Mass times Acceleration.” • Prototypical usage of individual things or actions: “What is a bicycle?” – “The thing, that man over there just crashed with.” • Functional mapping: “What is a bicycle?” – “A bicycle serves as a means of transport.” Samstag, 18. Juli 2009
    28. Knowledge sources Samstag, 18. Juli 2009
    29. Problem solving knowledge Knowledge sources Samstag, 18. Juli 2009
    30. Explanation knowledge Problem solving knowledge Knowledge sources Samstag, 18. Juli 2009
    31. Conceptual explanations Samstag, 18. Juli 2009
    32. Samstag, 18. Juli 2009
    33. Samstag, 18. Juli 2009
    34. Questions about retrieval results Samstag, 18. Juli 2009
    35. Questions about retrieval results • How did the system come to the similarity assessment of a particular case? Samstag, 18. Juli 2009
    36. Questions about retrieval results • How did the system come to the similarity Action assessment of a particular case? explanations Samstag, 18. Juli 2009
    37. Questions about retrieval results • How did the system come to the similarity Action assessment of a particular case? explanations • Which are the most similar aspects of a case? Which are the least? Samstag, 18. Juli 2009
    38. Action explanations • Action explanations explain the activities of the respective system. • Action explanations: “Why was this seat post selected?” – “For the given price, only one other seat post was available. But this was too short. • Negative action explanations: “Why was no carrier chosen?” – “A carrier is only available for touring bikes. The user did not choose a touring bike.” Samstag, 18. Juli 2009
    39. Samstag, 18. Juli 2009
    40. Samstag, 18. Juli 2009
    41. • Conceptual Explanations provide links to known concepts. Samstag, 18. Juli 2009
    42. • Conceptual Explanations provide links to known concepts. Samstag, 18. Juli 2009
    43. • Conceptual Explanations provide links to known concepts. Samstag, 18. Juli 2009
    44. • Conceptual Explanations provide links to known concepts. Samstag, 18. Juli 2009
    45. • Conceptual Explanations provide links to known concepts. • Action explanations provide information about the similarity calculation process. Samstag, 18. Juli 2009
    46. Most / least important aspects of a case Samstag, 18. Juli 2009
    47. Most / least important aspects of a case Samstag, 18. Juli 2009
    48. Explanation config panel Samstag, 18. Juli 2009
    49. Explanation config panel Samstag, 18. Juli 2009
    50. Questions during modelling and maintenance • Are some problem types underrepresented in the case base? • Is there an imbalance of cases in the case base? Samstag, 18. Juli 2009
    51. Samstag, 18. Juli 2009
    52. Samstag, 18. Juli 2009
    53. How many cases use a given attribute? Samstag, 18. Juli 2009
    54. How many cases use a given attribute? Samstag, 18. Juli 2009
    55. Distribution of cases regarding ‚manufacturer‘ Samstag, 18. Juli 2009
    56. Distribution of cases regarding ‚manufacturer‘ Samstag, 18. Juli 2009
    57. General system approach Samstag, 18. Juli 2009
    58. Samstag, 18. Juli 2009
    59. Take home messages Samstag, 18. Juli 2009
    60. Take home messages • Explanations are important and need to be considered while developing a software system. Samstag, 18. Juli 2009
    61. Take home messages • Explanations are important and Explainer need to be considered while User developing a software system. Originator • Explanations are part of communication scenario Samstag, 18. Juli 2009
    62. Take home messages • Explanations are important and Explainer need to be considered while User developing a software system. Originator • Explanations are part of communication scenario • Conceptual explanations support domain understanding. Samstag, 18. Juli 2009
    63. Take home messages • Explanations are important and Explainer need to be considered while User developing a software system. Originator • Explanations are part of communication scenario • Conceptual explanations support domain understanding. • Action explanations counteract encapsulation and information hiding. Samstag, 18. Juli 2009
    64. Take home messages • Explanations are important and Explainer need to be considered while User developing a software system. Originator • Explanations are part of communication scenario • Conceptual explanations support domain understanding. • Action explanations counteract encapsulation and information hiding. • Explanation manager provides access to conceptual and action explanations. Samstag, 18. Juli 2009
    65. Thank you! CAMBRIDGE, UK, 9 DEC 2008 Explanation Capabilities of the Open Source Case-Based Reasoning Tool myCBR Thomas Roth-Berghofer Senior researcher, trb@dfki.de German Research Centre for Artificial Intelligence DFKI GmbH Samstag, 18. Juli 2009
    66. Invitation to participate • ExaCt mailing list: http://groups.yahoo.com/group/explanation-research/ • ExaCt 2009 @ IJCAI 2009 http://exact2009.workshop.hm Samstag, 18. Juli 2009
    67. Publications of ExaCt research group 2008 2007 (contd.) [Bahls, 2008] Bahls, D. (2008). Explanation support for the case-based [Roth-Berghofer et al., 2007] Roth-Berghofer, T. R., Schulz, S., and Leake, reasoning tool myCBR. Project thesis, University of Kaiserslautern. D. B., editors (2007). Proceedings of the AAAI-07 workshop on [Forcher et al., 2008] Forcher, B., Adrian, B., and Roth-Berghofer, T. (2008). Explanation-aware Computing ExaCt2007. AAAI Press. Technical Report Explanations in the information extraction system iDocument. Künstliche WS-07-06. Intelligenz, 22(2). 2006 [Mittag, 2008] Mittag, F. (2008). ReduxExp: A justification-based [Richter et al., 2006] Richter, M. M., Roth-Berghofer, T., and Schulz, S., explanation-support server. Project thesis, University of Kaiserslautern. editors (2006). Explanation-aware Computing, volume 25. SAP - Slovak [Roth-Berghofer and Bahls, 2008] Roth-Berghofer, T. R. and Bahls, D. Academic Press Ltd., Bratislava. (2008). Code tagging and retrieval with myCBR. In Petridis, M., Coenen, F., 2005 and Bramer, M., editors, Research and Development in Intelligent Systems [Roth-Berghofer et al., 2005a] Roth-Berghofer, T., Cassens, J., and Sørmo, XXV, London, UK. Springer Verlag. F. (2005a). Goals and kinds of explanations in case-based reasoning. In [Roth-Berghofer and Mittag, 2008] Roth-Berghofer, T. R. and Mittag, F. Althoff, K.-D., Dengel, A., Bergmann, R., Nick, M., and Roth-Berghofer, T., (2008). ReduxExp: A justification-based explanation-support server. editors, WM 2005: Professional Knowledge Management, pages 264–268, Proceedings of AI-2008. the twenty-eighth SGAI international conference Kaiserslautern, Germany. DFKI GmbH. on artificial intelligence. In Petridis, M., Coenen, F., and Bramer, M., editors, [Roth-Berghofer and Cassens, 2005] Roth-Berghofer, T. R. and Cassens, J. Research and Development in Intelligent Systems XXV, London, UK. (2005). Mapping goals and kinds of explanations to the knowledge Springer Verlag. containers of case-based reasoning systems. In Muñoz-Avila, H. and Ricci, [Roth-Berghofer and Richter, 2008a] Roth-Berghofer, T. R. and Richter, M. F., editors, Case-Based Reasoning Research and Developmen, pages 451– M., editors (2008a). Künstliche Intelligenz—Topic: Explanation, volume 22, 464, Heidelberg. Springer Verlag. Bremen. BöttcherIT Verlag. [Roth-Berghofer et al., 2005b] Roth-Berghofer, T. R., Schulz, S., and [Roth-Berghofer and Richter, 2008b] Roth-Berghofer, T. R. and Richter, M. Woody, A., editors (2005b). Proceedings of the AAAI Fal l Symposium on M. (2008b). On explanation. Künstliche Intelligenz, 22(2):5–7. Explanation-aware Computing ExaCt2005. AAAI Press. Technical Report 2007 FS-05-04. [Bahls and Roth-Berghofer, 2007] Bahls, D. and Roth-Berghofer, T. (2007). 2004 Explanation support for the case-based reasoning tool myCBR. In [Roth-Berghofer, 2004] Roth-Berghofer, T. R. (2004). Explanations and Proceedings of the Twenty-Second AAAI Conference on Artificial Case-Based Reasoning: Foundational issues. In Funk, P. and González- Intelligence. July 22–26, 2007, Vancouver, British Columbia, Canada., Calero, P. A., editors, Advances in Case-Based Reasoning, pages 389–403. pages 1844–1845. The AAAI Press, Menlo Park, California. Springer-Verlag. [Eppert, 2007] Eppert, M. (2007). Generating provenance explanations for the gnowsis rebirth machine - a first pass. Pro ject thesis, University of Kaiserslautern. Samstag, 18. Juli 2009

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