Skip to main content
SpringerLink
Log in

Validation and Explanation

  • Chapter
  • First Online:
A Guided Tour of Artificial Intelligence Research

Abstract

Knowledge Based systems (KBS) that succeeded to expert systems are used nowadays to face different decision problems. Their architecture separates the modular and declarative knowledge of an application domain from its control using inference algorithms. This architecture requires a specific validation approach. KBS have been also the basis of many systems for which the explanation of computed results are almost as important as the results themselves. The aim of this chapter is to show the issues and the solutions to valid KBS and their use to explain reasoning.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

Notes

  1. 1.

    http://www.incose.org/AboutSE/WhatIsSE.

  2. 2.

    https://www.w3.org/standards/semanticweb/.

  3. 3.

    http://w3c.github.io/developers/tools/.

  4. 4.

    https://validator.w3.org/unicorn/.

  5. 5.

    https://www.w3.org/TR/2015/WD-vocab-dqv-20150625/.

  6. 6.

    https://www.w3.org/TR/2013/REC-prov-dm-20130430/.

  7. 7.

    https://www.w3.org/2005/Incubator/socialweb/XGR-socialweb-20101206/.

References

  • Acosta M, Zaveri A, Simperl E, Kontokostas D, Auer S, Lehmann J (2013) Crowdsourcing linked data quality assessment. In: The semantic web - ISWC 2013 - 12th international semantic web conference, Sydney, NSW, Australia, October 21–25, 2013, Proceedings, Part II, pp 260–276

    Google Scholar 

  • Aikins JS (1983) Prototypical knowledge for expert systems. Artif Intell 20:163–210

    Article  Google Scholar 

  • Allemandou J, Charnay L, Devillers L, Lauvergne M, Mariani J (2007) Simdial - un paradigme pour évaluer automatiquement des systèmes de dialogue homme-machine en simulant un utilisateur de façon déterministe. Traitement Automatique des Langues, 48:1 Principes de l’évaluation en Traitement Automatique des Langues

    Google Scholar 

  • Ayel M, Rousset M (1990) La cohérence dans les bases de connaissances. Editions Cépaduès

    Google Scholar 

  • Bader S (2013) Generating explanations for Pro-active assistance from formal action descriptions. Springer International Publishing, Cham, pp 19–31

    Google Scholar 

  • Bahill AT, Gissing B (1998) Re-evaluating systems engineering concepts using systems thinking. IEEE Trans Syst Man Cybern Part C 28(4):516–527

    Article  Google Scholar 

  • Baker M (2009). Argumentative interactions and the social construction of knowledge. In: Argumentation and Education: Theoretical Foundations and Practices, San Francisco, CA, USA. N.M. Mirza and A.-N. Perret-Clermont, Springer, Berlin, pp. 127–144

    Google Scholar 

  • Baker M, Charnay L, Joab M, Lemaire B, Safar B, Schlienger D (1996) Incorporating functionalities of expert medical critiquing dialogues in the design of a graphical interface. In: 2012 IEEE 24th International Conference on Tools with Artificial Intelligence, 0:122

    Google Scholar 

  • Beauvieux A, Dague P (1990) A general consistency (checking and restoring) engine for knowledge bases. In: European conference of artificial intelligence ECAI’90, pp 77–82

    Google Scholar 

  • Bex F, Walton D, Budzynska K (2012) Argument and explanation in the context of dialogue. In: Explanation-aware computing, papers from the 2012 ECAI workshop, Montpellier, France, July 28, 2012, pp 6–10

    Google Scholar 

  • Biran O, Cotton C (2017) Explanation and justification in machine learning: A survey. In: Proceedings of the workshop on explainable AI (XAI), IJCAI, pp 8–13

    Google Scholar 

  • Bonatti PA, Olmedilla D, Peer J (2006) Advanced policy explanations on the web. In: Proceeding of the 2006 conference on ECAI 2006, Amsterdam, The Netherlands, IOS Press, pp 200–204

    Google Scholar 

  • Bouali F (1996) Diagnostic, validation et réparation de bases de connaissances : le système KBDR, Université PARIS-XI, centre d’Orsay, PhD thesis

    Google Scholar 

  • Bouaud J, Séroussi B, Brizon A (2008) Impact de la réactualisation de recommandations de pratiques cliniques sur l’évolution d’une base de connaissances. In: Actes des 19es Journées Francophones d’Ingénierie des Connaissances (IC 2008) 19es Journées Francophones d’Ingénierie des Connaissances (IC 2008), Nancy, France, pp 1–12

    Google Scholar 

  • Brank J, Grobelnik M, Mladenic D (2005) A survey of ontology evaluation techniques. In: Proceedings of the conference on data mining and data warehouses (SiKDD)

    Google Scholar 

  • Brewster C, Alani H, Dasmahapatra S, Wilks Y (2004) Data driven ontology evaluation. In: Proceedings of the fourth international conference on language resources and evaluation, LREC 2004, May 26-28, 2004, Lisbon, Portugal

    Google Scholar 

  • Brinton C (2017) A framework for explanation of machine learning decisions. In: Proceedings of the workshop on explainable AI (XAI), IJCAI, pp 14–18

    Google Scholar 

  • Cabrio E, Villata S, Gandon F (2013) A support framework for argumentative discussions management in the web. In: The semantic web: semantics and big data, 10th international conference, ESWC 2013, Montpellier, France, May 26–30, 2013. Proceedings, pp 412–426

    Google Scholar 

  • Cawsey A (1990) Generating explanatory discourse. In: Current research in natural language generation. Academic Press Professional Inc., San Diego, CA, USA, pp 75–101

    Google Scholar 

  • Charnay L (1999) Dialogue et explication dans les Systèmes à base de connaissances : ADex, un modèle informatique pour l’énonciation, PhD thesis, Université PARIS-XI, centre d’Orsay, notes et documents LIMSI num, pp 99–19

    Google Scholar 

  • Chatalic P, Nguyen GH, Rousset M-C (2006) Reasoning with inconsistencies in propositional peer-to-peer inference systems. In: ECAI, pp 352–356

    Google Scholar 

  • Chen L, Pu P (2012) Critiquing-based recommenders: survey and emerging trends. User Model User-Adapt Interact 22(1–2):125–150

    Article  Google Scholar 

  • Clancey WJ (1986) From guidon to neomycin and heracles in twenty short lessons. AI Mag 7(3):40–60

    Google Scholar 

  • Corby O, Dieng-Kuntz R, Faron-Zucker C, Gandon F (2006) Searching the semantic web: approximate query processing based on ontologies. IEEE Intell Syst 21(1):20–27

    Article  Google Scholar 

  • David J (1995) Les systèmes experts de seconde génération. TSI 14(4):435–471

    MathSciNet  Google Scholar 

  • Dessalles J-L (2008) La pertinence et ses origines cognitives - Nouvelles théories. Hermès-Science, Paris, France

    Google Scholar 

  • Devillers L, Bonneau-Maynard H, Rosset S, Paroubek P, McTait K, Mostefa D, Choukri K, Charnay L, Bousquet C, Vigouroux N, Bchet, F., Romary, L, Antoine, J-Y, Villaneau, J., Vergnes, M., and Goulian, J (2004) The French MEDIA/EVALDA Project: the Evaluation of the Understanding Capability of Spoken Language Dialogue Systems. In: LREC, Lisbon

    Google Scholar 

  • Dibie-Barthélemy J, Haemmerlé O, Salvat E (2006) A semantic validation of conceptual graphs. Knowl Based Syst 19(7):26–38

    Article  Google Scholar 

  • Djedidi R, Aufaure M (2010) ONTO-EVO\({}^{\text{a}}\)L an ontology evolution approach guided by pattern modeling and quality evaluation. In: Foundations of information and knowledge systems, 6th international symposium, FoIKS 2010, Sofia, Bulgaria, February 15–19, 2010, Proceedings, pp 286–305

    Google Scholar 

  • Djedidi R, Aufaure M-A (2009) Patrons de gestion de changements OWL. In: Ingénierie des connaissances. Hammamet, Tunisia, pp 145–156

    Google Scholar 

  • Duque-Ramos A, Fernández-Breis JT, Iniesta-Moreno M, Dumontier M, Aranguren ME, Schulz S, Aussenac-Gilles N, Stevens R (2013) Evaluation of the oquare framework for ontology quality. Expert Syst Appl 40(7):2696–2703

    Article  Google Scholar 

  • Euzenat J, Shvaiko P (2007) Ontology matching. Springer, Berlin

    Google Scholar 

  • Farreny H (1985) Les systèmes experts. Cepadues

    Google Scholar 

  • Feigenbaum E, Buchanan B, Lederberg J (1971) On generality and problem solving: a case study using the dendral program. Mach Intell 6:165–190

    Google Scholar 

  • Gangemi A, Catenacci C, Ciaramita M, Lehmann J (2006) Modelling ontology evaluation and validation. In: The semantic web: research and applications, 3rd European semantic web conference, ESWC 2006, Budva, Montenegro, June 11–14, 2006, Proceedings, pp 140–154

    Google Scholar 

  • Gangemi A, Presutti V (2009) Ontology design patterns. In: Handbook on ontologies pp 221–243

    Google Scholar 

  • Ginsberg A (1988) Knowledge-base reduction : a new approach to checking knowledge bases for inconsistency and redundancy. In: National conference of american association of artificial intelligence AAAI’88, pp 585–589

    Google Scholar 

  • Gómez-Pérez A (2004) Ontology evaluation. In: Handbook on ontologies, pp 251–274

    Google Scholar 

  • Guarino N, Welty CA (2004) An overview of ontoclean. In: Handbook on ontologies, pp 151–172

    Google Scholar 

  • Haouche C, Charlet J (1996) KBS validation : a knowledge acquisition perspective. In: European conference of artificial intelligence ECAI’96, pp 433–437

    Google Scholar 

  • Haynes SR, Cohen MA, Ritter FE (2009) Designs for explaining intelligent agents. Int J Hum Comput Stud 67(1):90–110

    Article  Google Scholar 

  • Hors P, Rousset M (1996) Modeling and verifying complex objects : a declarative approach based on description logics. In: European conference of artificial intelligence ECAI’96, pp 328–332

    Google Scholar 

  • Hovy EH (1988) Planning coherent multisentential text. In: Proceedings of the 26th annual meeting of the association for computational linguistics, Association for Computational Linguistics, Buffalo, New York, USA, pp 163–169

    Google Scholar 

  • Institut PM (2013) Project Management Institut

    Google Scholar 

  • Kassel G (1987) The use of deep knowledge to improve explanation capabilities of rule-based expert systems. In: Expertensysteme, pp 315–326

    Google Scholar 

  • Kontokostas D, Westphal P, Auer S, Hellmann S, Lehmann J, Cornelissen R, Zaveri A (2014) Test-driven evaluation of linked data quality. In: 23rd international world wide web conference, www ’14, Seoul, Republic of Korea, April 7-11, 2014, pp 747–758

    Google Scholar 

  • Lane HC, Core MG, van Lent M, Solomon S, Gomboc D (2005). Explainable artificial intelligence for training and tutoring. In: Proceeding of the 2005 conference on artificial intelligence in education, pp 762–764, IOS Press, Amsterdam, The Netherlands,

    Google Scholar 

  • Lee J, Lai LF, Yang S (2002) A high-level petri nets-based approach to verifying task structures. IEEE Trans. Knowl Data Eng 14(2):316–335

    Article  Google Scholar 

  • Loiseau S (1998) Validation, mise au point et interaction: quelques solutions pour assister le concepteur de bases de connaissances et l’utilisateur de systèmes informatiques. In: Habilitation à diriger des recherches

    Google Scholar 

  • Lopez V, Unger C, Cimiano P, Motta E (2013) Evaluating question answering over linked data. J Web Semant 21:3–13

    Article  Google Scholar 

  • Baker M, Dessalles J-L, Joab M, Raccah P-Y, Safar B, Schlienger D (1995) La génération d’explications négociées dans un système à base de connaissances. In: Actes des 5èmes journées nationales du PRC-GDR intelligence artificielle, pp 297–316

    Google Scholar 

  • McKeown KR (1985) Discourse strategies for generating natural-language text. Artif Intell 27:1–41

    Article  Google Scholar 

  • Minsky M (1975) A framework for representing knowledge. In: The psychology of computer vision, pp 211–285

    Google Scholar 

  • MoDeVA (2009) Workshop model design and validation of models

    Google Scholar 

  • Moreau L, Groth PT, Cheney J, Lebo T, Miles S (2015) The rationale of PROV. J Web Sem 35:235–257

    Article  Google Scholar 

  • Mugnier M, Chein M (1996) Représenter des connaissances et raisonner avec des graphes. Revue d’Intelligence Artificielle 7(1):7–56

    MATH  Google Scholar 

  • Neches R, Swartout WR, Moore J (1985) Explainable (and maintainable) expert systems. In: IJCAI’85: proceedings of the 9th international joint conference on artificial intelligence. Morgan Kaufmann Publishers Inc, San Francisco, pp 382–389

    Google Scholar 

  • Nguyen GH, Chatalic P, Rousset M-C (2008) A probabilistic trust model for semantic peer-to-peer systems. In: ECAI, pp 881–882

    Google Scholar 

  • Nguyen TA, Perkins WA., Laffrey TJ, Pecora D (1985) Checking an expert system knowledge base for consistency and completness. In: International join conference of artificial intelligence, IJCAI’85, vol 1, pp 375–378

    Google Scholar 

  • Nkambou R, Bourdeau J, Mizoguchi R (2010) Advances in intelligent tutoring systems. Springer. Berlin

    Google Scholar 

  • Obrst L, Ceusters W, Mani I, Ray S, Smith B (2007) The evaluation of ontologies. In: Baker CJO, Cheung K-H (eds) Semantic web: revolutionizing knowledge discovery in the life sciences. Springer, Berlin, pp 139–158

    Google Scholar 

  • Paris C, Cecile L, Swartout WR, Mann WC (eds) (1990) Natural language generation in artificial intelligence and computational linguistics. Kluwer Academic Publishers, Norwell

    Google Scholar 

  • Paris CL, McKeown KR (1987) Discourse strategies for describing complex physical objects. Springer, Netherlands, pp 97–115

    Google Scholar 

  • Paris CL, Swartout WR, Mann WC (eds) (1991) Natural language generation in artificial intelligence and computational linguistics. Kluwer, Boston

    MATH  Google Scholar 

  • Pipard (1987) INDE: un système de détection d’inconsistances et d’incomplétudes dans les bases de connaissances. PhD thesis, Université PARIS-XI, centre d’Orsay

    Google Scholar 

  • Poveda-Villalón M, Gómez-Pérez A, Suárez-Figueroa MC (2014) Oops! (ontology pitfall scanner!): an on-line tool for ontology evaluation. Int J Sem Web Inf Syst 10(2):7–34

    Article  Google Scholar 

  • Presutti V, Blomqvist E, Daga E, Gangemi A (2012) Pattern-based ontology design. In: Ontology engineering in a networked World, pp 35–64

    Google Scholar 

  • Rahwan I, Zablith F, Reed C (2007) Laying the foundations for a world wide argument web. Artif Intell 171(10–15):897–921

    Article  Google Scholar 

  • Rao, J. and Su, X. (2004). A survey of automated web service composition methods. In: Semantic web services and web process composition, first international workshop, SWSWPC 2004, San Diego, CA, USA, July 6, 2004, Revised selected papers, pp 43–54

    Google Scholar 

  • Reiter R (1987) A theory of diagnosis from first principles. Artif Intell 32:57–95

    Article  MathSciNet  MATH  Google Scholar 

  • Reiter R, de Kleer J (1987) Foundations of assumption-based truth maintenance system. In: AAAI, pp 183–188

    Google Scholar 

  • Roth-Berghofer T, Leake DB, Cassens J (eds) (2012) Explanation-aware computing, papers from the 2012 ECAI Workshop, Montpellier, France, July 28, 2012

    Google Scholar 

  • Roth-Berghofer T, Schulz S (eds) (2005) Explanation-aware computing, papers from the 2005 AAAI fall symposium, November 4–6, 2005, Arlington, Virginia. AAAI technical report, vol FS-05-04. AAAI Press

    Google Scholar 

  • Roth-Berghofer T, Schulz S, Bahls D, Leake DB (eds) (2007) Explanation-aware computing, papers from the 2007 AAAI workshop, Vancouver, British Columbia, Canada, July 22–23, 2007. AAAI Technical Report, vol WS-07-06. AAAI Press

    Google Scholar 

  • Roth-Berghofer T, Schulz S, Leake DB, Bahls D (eds) (2008) Explanation-aware computing, papers from the 2008 ECAI Workshop, Patras, Greece, July 21–22, 2008. University of Patras

    Google Scholar 

  • Roth-Berghofer T, Tintarev N, Leake DB (eds) (2009) Explanation-aware computing, papers from the 2009 IJCAI workshop, Pasadena, California , USA, July 11–12, 2009

    Google Scholar 

  • Roth-Berghofer T, Tintarev N, Leake DB (eds) (2011) Explanation-aware Computing, Papers from the 2011 IJCAI Workshop, Barcelona, Spain, July 16–17, 2011

    Google Scholar 

  • Roth-Berghofer T, Tintarev N, Leake DB, Bahls D (eds) (2010) Explanation-aware Computing, Papers from the 2010 ECAI Workshop, Lisbon, Portugal, August 16, 2010. University of Lisbon, Portugal

    Google Scholar 

  • Rousset M (1988) On the consistency of knowledge bases: the COVADIS system. In: European conference of artificial intelligence ECAI’88, pp 79–84

    Google Scholar 

  • Rousset M, Levy A (1996) Verification of knowledge bases based on containment checking. In: National conference of American association of artificial intelligence AAAI’96, pp 585–591

    Google Scholar 

  • Rousset M, Levy A (1998) Verification of knowledge bases based on containment checking. Artif Intell 101(1–2):227–250

    MathSciNet  MATH  Google Scholar 

  • Safar B (1987) Le problème des explications négatives dans les Systèmes Experts: Le système POURQUOI-PAS? PhD thesis, Université PARIS-XI, centre d’Orsay

    Google Scholar 

  • Schneider J, Groza T, Passant A (2013) A review of argumentation for the social semantic web. Sem Web 4(2):159–218

    Article  Google Scholar 

  • Schober D, Tudose I, Svatek V, Boeker M (2012) Ontocheck: verifying ontology naming conventions and metadata completeness in protégé 4. J Biomed Sem 3(2):1–10

    Google Scholar 

  • Shanks G, Tansley E, Weber R (2003) Using ontology to validate conceptual models. Commun ACM 46(10):85–89

    Article  Google Scholar 

  • Sheng QZ, Qiao X, Vasilakos AV, Szabo C, Bourne S, Xu X (2014) Web services composition: a decade’s overview. Inf Sci 280:218–238

    Article  Google Scholar 

  • Shortliffe EH (1976) Computer-based medical consultations: MYCIN. Kluwer Academic Publishers, Elsevier, New York

    Google Scholar 

  • Sombe L (1988) Raisonnements sur des informations incomplétes en intelligence artificielle. Revue d intelligence artificielle 2(3–4):9–210

    Google Scholar 

  • Sowa J (1984) Conceptual structures: information processing in mind and machine. Addison Wesley Publishing Company, Boston

    Google Scholar 

  • Staab S, Studer R (2009) Handbook on ontologies, 2nd edn. Springer, Berlin

    Google Scholar 

  • Steels L (1985) Second generation expert systems. Future Gener Comput Syst 1(4):213–221

    Article  Google Scholar 

  • Suárez-Figueroa MC, Gómez-Pérez A, Fernández-López M (2015) The neon methodology framework: a scenario-based methodology for ontology development. Appl Ontol 10(2):107–145

    Article  Google Scholar 

  • Sure Y, Staab S, Studer R (2009) Ontology engineering methodology. In: Staab S, Studer R (eds) Handbook on ontologies, 2nd edn. Springer, Berlin, pp 135–152

    Google Scholar 

  • Swartout W, Paris C, Moore J (1991) Explanations in knowledge systems: design for explainable expert systems. IEEE Expert: Intell Syst Appl 6(3):58–64

    Google Scholar 

  • Swartout WR (1983) Xplain: a system for creating and explaining expert consulting programs. Artif Intell 21:285–325

    Article  Google Scholar 

  • Thomopoulos R, Croitoru M, Tamani N (2015) Decision support for agri-food chains: a reverse engineering argumentation-based approach. Ecol Inf 26(2):182–191

    Article  Google Scholar 

  • Unger C, Forascu C, Lopez V, Ngomo AN, Cabrio E, Cimiano P, Walter S (2015) Question answering over linked data (QALD-5). In: Working notes of CLEF 2015 - conference and labs of the evaluation forum, Toulouse, France, September 8–11, 2015

    Google Scholar 

  • Vrandecic D (2009) Ontology evaluation. In: Staab S, Studer R (eds) Handbook on ontologies, 2nd edn. Springer, Berlin, pp 293–313

    Google Scholar 

  • Walton D (2007) Dialogical models of explanation. In: Explanation-aware computing, papers from the 2007 AAAI workshop, Vancouver, British Columbia, Canada, July 22–23, 2007, pp 1–9

    Google Scholar 

  • Weiner JL (1980) Blah, a system which explains its reasoning. Artif Intell 15(1–2):19–48

    Article  Google Scholar 

  • Wick MR, Thompson WB (1989) Reconstructive explanation: explanation as complex problem solving. In: IJCAI’89: proceedings of the 11th international joint conference on artificial intelligence. Morgan Kaufmann Publishers Inc, San Francisco, pp 135–140

    Google Scholar 

  • Yurchyshyna A, Faron-Zucker C, Mirbel I, Sall B, Thanh NL, Zarli A (2008) Une approche ontologique pour formaliser la connaissance experte dans le modèle du contrôle de conformité en construction. Actes d’IC 49–60

    Google Scholar 

  • Zaveri A, Rula A, Maurino A, Pietrobon R, Lehmann J, Auer S (2016) Quality assessment for linked data: a survey. Sem Web 7(1):63–93

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Orange Business Services, Paris, France

    Laurent Charnay

  2. UMR MIA-Paris, AgroParisTech, INRA, Université Paris-Saclay, 75005, Paris, France

    Juliette Dibie

  3. LERIA, Université Angers, Angers, France

    Stéphane Loiseau

Authors
  1. Laurent Charnay
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Juliette Dibie
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Stéphane Loiseau
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Laurent Charnay .

Editor information

Editors and Affiliations

  1. CRIL-CNRS, Université d'Artois and Institut Universitaire de France, Lens, France

    Pierre Marquis

  2. Aix Marseille Université, Université de Toulon, CNRS, LIS, Marseille, France

    Odile Papini

  3. IRIT, CNRS and Université Paul Sabatier, Toulouse, France

    Henri Prade

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Charnay, L., Dibie, J., Loiseau, S. (2020). Validation and Explanation . In: Marquis, P., Papini, O., Prade, H. (eds) A Guided Tour of Artificial Intelligence Research. Springer, Cham. https://doi.org/10.1007/978-3-030-06164-7_22

Download citation

Publish with us

Policies and ethics

Search

Navigation