{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T11:59:08Z","timestamp":1776081548373,"version":"3.50.1"},"reference-count":33,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2021,1,7]],"date-time":"2021-01-07T00:00:00Z","timestamp":1609977600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2021,1,7]],"date-time":"2021-01-07T00:00:00Z","timestamp":1609977600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100005416","name":"Research Council of Norway","doi-asserted-by":"crossref","award":["00"],"award-info":[{"award-number":["00"]}],"id":[{"id":"10.13039\/501100005416","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Prog Artif Intell"],"published-print":{"date-parts":[[2021,3]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>This paper presents the inference and reasoning methods in a Bayesian supported knowledge-intensive case-based reasoning (CBR) system called BNCreek. The inference and reasoning process in this system is a combination of three methods. The semantic network inference methods and the CBR method are employed to handle the difficulties of inferencing and reasoning in uncertain domains. The Bayesian network inference methods are employed to make the process more accurate. An experiment from oil well drilling as a complex and uncertain application domain is conducted. The system is evaluated against expert estimations and compared with seven other corresponding systems. The normalized discounted cumulative gain (NDCG) as a rank-based metric, the weighted error (WE), and root-square error (RSE) as the statistical metrics are employed to evaluate different aspects of the system capabilities. The results show the efficiency of the developed inference and reasoning methods.<\/jats:p>","DOI":"10.1007\/s13748-020-00223-1","type":"journal-article","created":{"date-parts":[[2021,1,7]],"date-time":"2021-01-07T21:03:26Z","timestamp":1610053406000},"page":"49-63","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Inference and reasoning in a Bayesian knowledge-intensive CBR system"],"prefix":"10.1007","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4705-9475","authenticated-orcid":false,"given":"Hoda","family":"Nikpour","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Agnar","family":"Aamodt","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,1,7]]},"reference":[{"key":"223_CR1","doi-asserted-by":"crossref","unstructured":"Aamodt, A.: Knowledge-intensive case-based reasoning in Creek. In: European Conference on Case-Based Reasoning, pp. 1\u201315, Springer (2004)","DOI":"10.1007\/978-3-540-28631-8_1"},{"issue":"2","key":"223_CR2","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1017\/S026988890200019X","volume":"17","author":"C Lacave","year":"2002","unstructured":"Lacave, C., D\u00edez, F.J.: A review of explanation methods for bayesian networks. Knowl. Eng. Rev. 17(2), 107\u2013127 (2002)","journal-title":"Knowl. Eng. Rev."},{"issue":"2","key":"223_CR3","doi-asserted-by":"publisher","first-page":"75","DOI":"10.5430\/air.v1n2p75","volume":"1","author":"FJM Velasco","year":"2012","unstructured":"Velasco, F.J.M.: A bayesian network approach to diagnosing the root cause of failure from trouble tickets. Artif. Intell. Res. 1(2), 75\u201385 (2012)","journal-title":"Artif. Intell. Res."},{"key":"223_CR4","volume-title":"An Introduction to Bayesian Networks","author":"FV Jensen","year":"1996","unstructured":"Jensen, F.V., et al.: An Introduction to Bayesian Networks, vol. 210. UCL Press, London (1996)"},{"key":"223_CR5","volume-title":"Plausible Inheritance; Semantic Network Inference for Case-based Reasoning","author":"F S\u00f8rmo","year":"2000","unstructured":"S\u00f8rmo, F.: Plausible Inheritance; Semantic Network Inference for Case-based Reasoning. Department of Computer and Information Science, Norwegian University of Science and Technology, Trondheim (2000)"},{"key":"223_CR6","doi-asserted-by":"crossref","unstructured":"Nikpour, H., Aamodt, A., Bach, K.: Bayesian-supported retrieval in BNCreek: a knowledge-intensive case-based reasoning system. In: International Conference on Case-Based Reasoning, pp. 323\u2013338, Springer (2018)","DOI":"10.1007\/978-3-030-01081-2_22"},{"key":"223_CR7","unstructured":"Nikpour, H., Aamodt, A., Skalle, P.: Diagnosing root causes and generating graphical explanations by integrating temporal causal reasoning and CBR. In: CEUR Workshop Proceedings (2017)"},{"key":"223_CR8","unstructured":"Bach, K., Sauer, C., Althoff, K.-D., Roth-Berghofer, T.: Knowledge modelling with the open source tool myCBR. In: CEUR Workshop Proceedings (2014)"},{"key":"223_CR9","unstructured":"Kim, B., Rudin, C., Shah, J. A.: The Bayesian case model: a generative approach for case-based reasoning and prototype classification. In: Advances in Neural Information Processing Systems, pp. 1952\u20131960, (2014)"},{"key":"223_CR10","doi-asserted-by":"publisher","first-page":"213","DOI":"10.1016\/j.isatra.2018.12.049","volume":"90","author":"Y Guo","year":"2019","unstructured":"Guo, Y., Chen, W., Zhu, Y.-X., Guo, Y.-Q.: Research on the integrated system of case-based reasoning and Bayesian network. ISA Trans. 90, 213\u2013225 (2019)","journal-title":"ISA Trans."},{"key":"223_CR11","unstructured":"Cain, T., Pazzani, M. J., Silverstein, G.: Using domain knowledge to influence similarity judgements. In: Proceedings of the Case-Based Reasoning Workshop, pp. 191\u2013198 (1991)"},{"issue":"4","key":"223_CR12","doi-asserted-by":"publisher","first-page":"327","DOI":"10.1037\/0033-295X.84.4.327","volume":"84","author":"A Tversky","year":"1977","unstructured":"Tversky, A.: Features of similarity. Psychol. Rev. 84(4), 327 (1977)","journal-title":"Psychol. Rev."},{"issue":"1","key":"223_CR13","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1080\/00291463.1959.10780403","volume":"11","author":"H Eisler","year":"1959","unstructured":"Eisler, H., Ekman, G.: A mechanism of subjective similarity. Nordisk Psykologi 11(1), 1\u201310 (1959)","journal-title":"Nordisk Psykologi"},{"key":"223_CR14","volume-title":"Psychometrics of Similarity","author":"RAM Gregson","year":"1975","unstructured":"Gregson, R.A.M.: Psychometrics of Similarity. Academic Press, Cambridge (1975)"},{"issue":"6","key":"223_CR15","doi-asserted-by":"publisher","first-page":"413","DOI":"10.1037\/h0054576","volume":"58","author":"RR Bush","year":"1951","unstructured":"Bush, R.R., Mosteller, F.: A model for stimulus generalization and discrimination. Psychol. Rev. 58(6), 413 (1951)","journal-title":"Psychol. Rev."},{"key":"223_CR16","doi-asserted-by":"publisher","first-page":"249","DOI":"10.1007\/978-94-011-3488-0_12","volume-title":"Automated Reasoning","author":"MM Richter","year":"1991","unstructured":"Richter, M.M., Wess, S.: Similarity, uncertainty and case-based reasoning in patdex. In: Boyer, R.S. (ed.) Automated Reasoning, pp. 249\u2013265. Springer, Dordrecht (1991)"},{"key":"223_CR17","unstructured":"Aha, D.W., Chang, L.W.: Cooperative Bayesian and case-based reasoning for solving multiagent planning tasks. Navy Center for, Citeseer (1996)"},{"key":"223_CR18","volume-title":"The Mathematics of Inheritance Systems","author":"DS Touretzky","year":"1986","unstructured":"Touretzky, D.S.: The Mathematics of Inheritance Systems, vol. 8. Morgan Kaufmann, Burlington (1986)"},{"key":"223_CR19","unstructured":"Aamodt, A.: A knowledge-intensive, integrated approach to problem solving and sustained learning. Knowledge Engineering and Image Processing Group. University of Trondheim, pp. 27\u201385 (1991)"},{"issue":"1","key":"223_CR20","doi-asserted-by":"publisher","first-page":"39","DOI":"10.3233\/AIC-1994-7104","volume":"7","author":"A Aamodt","year":"1994","unstructured":"Aamodt, A., Plaza, E.: Case-based reasoning: foundational issues, methodological variations, and system approaches. AI Commun. 7(1), 39\u201359 (1994)","journal-title":"AI Commun."},{"key":"223_CR21","unstructured":"Swartout, W.R.: Rule-based expert systems: The mycin experiments of the stanford heuristic programming project: BG Buchanan and EH Shortliffe, (Addison-Wesley, Reading, MA, 1984); 702 pages, $${\\$}\\,$$40.50 (1985)"},{"issue":"1","key":"223_CR22","doi-asserted-by":"publisher","first-page":"269","DOI":"10.1007\/BF01386390","volume":"1","author":"EW Dijkstra","year":"1959","unstructured":"Dijkstra, E.W., et al.: A note on two problems in connexion with graphs. Numer. Math. 1(1), 269\u2013271 (1959)","journal-title":"Numer. Math."},{"issue":"2\u20133","key":"223_CR23","doi-asserted-by":"publisher","first-page":"393","DOI":"10.1016\/0004-3702(90)90060-D","volume":"42","author":"GF Cooper","year":"1990","unstructured":"Cooper, G.F.: The computational complexity of probabilistic inference using Bayesian belief networks. Artif. Intell. 42(2\u20133), 393\u2013405 (1990)","journal-title":"Artif. Intell."},{"issue":"1","key":"223_CR24","doi-asserted-by":"publisher","first-page":"141","DOI":"10.1016\/0004-3702(93)90036-B","volume":"60","author":"P Dagum","year":"1993","unstructured":"Dagum, P., Luby, M.: Approximating probabilistic inference in bayesian belief networks is NP-hard. Artif. Intell. 60(1), 141\u2013153 (1993)","journal-title":"Artif. Intell."},{"key":"223_CR25","unstructured":"Paskin, M.: A short course on graphical models: 3. The junction tree algorithms. Short Course notes http:\/\/ai.stanford.edu\/paskin\/gm-short-course\/lec3.pdf (May 30, 2010) (2003)"},{"issue":"2","key":"223_CR26","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1111\/j.2517-6161.1988.tb01721.x","volume":"50","author":"SL Lauritzen","year":"1988","unstructured":"Lauritzen, S.L., Spiegelhalter, D.J.: Local computations with probabilities on graphical structures and their application to expert systems. J. Roy. Stat. Soc.: Ser. B (Methodol.) 50(2), 157\u2013194 (1988)","journal-title":"J. Roy. Stat. Soc.: Ser. B (Methodol.)"},{"key":"223_CR27","unstructured":"Barber, D.: Probabilistic modelling and reasoning: the junction tree algorithm. Course Notes (2004)"},{"key":"223_CR28","volume-title":"Pattern Recognition and Machine Learning by Christopher M. Bishop","author":"CM Bishop","year":"2006","unstructured":"Bishop, C.M.: Pattern Recognition and Machine Learning by Christopher M. Bishop. Springer, Berlin (2006)"},{"key":"223_CR29","first-page":"953","volume-title":"Semantic Web","author":"R Carvalho","year":"2010","unstructured":"Carvalho, R., Laskey, K., Costa, P., Ladeira, M., Santos, L., Matsumoto, S.: Unbbayes: modeling uncertainty for plausible reasoning in the semantic web. In: Wu, G. (ed.) Semantic Web, pp. 953\u2013978. Rijeka, InTech (2010)"},{"key":"223_CR30","doi-asserted-by":"publisher","DOI":"10.1201\/b10391","volume-title":"Bayesian Artificial Intelligence","author":"KB Korb","year":"2010","unstructured":"Korb, K.B., Nicholson, A.E.: Bayesian Artificial Intelligence. CRC Press, Boca Raton (2010)"},{"issue":"4","key":"223_CR31","doi-asserted-by":"publisher","first-page":"267","DOI":"10.1080\/088395198117730","volume":"12","author":"TW Liao","year":"1998","unstructured":"Liao, T.W., Zhang, Z., Mount, C.R.: Similarity measures for retrieval in case-based reasoning systems. Appl. Artif. Intell. 12(4), 267\u2013288 (1998)","journal-title":"Appl. Artif. Intell."},{"issue":"3","key":"223_CR32","doi-asserted-by":"publisher","first-page":"317","DOI":"10.1007\/s10462-011-9310-2","volume":"41","author":"SV Shokouhi","year":"2014","unstructured":"Shokouhi, S.V., Skalle, P., Aamodt, A.: An overview of case-based reasoning applications in drilling engineering. Artif. Intell. Rev. 41(3), 317\u2013329 (2014)","journal-title":"Artif. Intell. Rev."},{"key":"223_CR33","doi-asserted-by":"crossref","unstructured":"Stahl, A., Roth-Berghofer, T.R.: Rapid prototyping of CBR applications with the open source tool myCBR. In: European conference on case-based reasoning, pp. 615\u2013629, Springer (2008)","DOI":"10.1007\/978-3-540-85502-6_42"}],"container-title":["Progress in Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s13748-020-00223-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s13748-020-00223-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s13748-020-00223-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,22]],"date-time":"2024-08-22T01:44:41Z","timestamp":1724291081000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s13748-020-00223-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,1,7]]},"references-count":33,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2021,3]]}},"alternative-id":["223"],"URL":"https:\/\/doi.org\/10.1007\/s13748-020-00223-1","relation":{},"ISSN":["2192-6352","2192-6360"],"issn-type":[{"value":"2192-6352","type":"print"},{"value":"2192-6360","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,1,7]]},"assertion":[{"value":"6 February 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 November 2020","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 January 2021","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}