{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T06:58:39Z","timestamp":1792738719744,"version":"4.5.0"},"publisher-location":"Cham","reference-count":92,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030292485","type":"print"},{"value":"9783030292492","type":"electronic"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-3-030-29249-2_11","type":"book-chapter","created":{"date-parts":[[2019,9,1]],"date-time":"2019-09-01T23:02:43Z","timestamp":1567378963000},"page":"155-171","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":60,"title":["How Case-Based Reasoning Explains Neural Networks: A Theoretical Analysis of XAI Using Post-Hoc Explanation-by-Example from a Survey of ANN-CBR Twin-Systems"],"prefix":"10.1007","author":[{"given":"Mark T.","family":"Keane","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eoin M.","family":"Kenny","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2019,8,9]]},"reference":[{"key":"11_CR1","doi-asserted-by":"publisher","first-page":"52138","DOI":"10.1109\/ACCESS.2018.2870052","volume":"6","author":"A Adadi","year":"2018","unstructured":"Adadi, A., Berrada, M.: Peeking inside the black-box: a survey on explainable artificial intelligence (XAI). IEEE Access 6, 52138\u201352160 (2018)","journal-title":"IEEE Access"},{"issue":"3","key":"11_CR2","doi-asserted-by":"publisher","first-page":"50","DOI":"10.1609\/aimag.v38i3.2741","volume":"38","author":"B Goodman","year":"2017","unstructured":"Goodman, B., Flaxman, S.: European Union regulations on algorithmic decision-making and a \u201cright to explanation\u201d. AI Mag. 38(3), 50\u201357 (2017)","journal-title":"AI Mag."},{"issue":"2","key":"11_CR3","doi-asserted-by":"publisher","first-page":"76","DOI":"10.1093\/idpl\/ipx005","volume":"7","author":"S Wachter","year":"2017","unstructured":"Wachter, S., Mittelstadt, B., Floridi, L.: Why a right to explanation of automated decision-making does not exist in the general data protection regulation. Int. Data Privacy Law 7(2), 76\u201399 (2017)","journal-title":"Int. Data Privacy Law"},{"key":"11_CR4","unstructured":"Kenny, E.M., Keane, M.T.: Twin-systems to explain neural networks using case-based reasoning. In: Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI 2019), pp. 326\u2013333 (2019)"},{"issue":"5","key":"11_CR5","doi-asserted-by":"publisher","first-page":"93","DOI":"10.1145\/3236009","volume":"51","author":"R Guidotti","year":"2018","unstructured":"Guidotti, R., Monreale, A., Ruggieri, S., Turini, F., Giannotti, F., Pedreschi, D.: A survey of methods for explaining black box models. ACM Comput. Surv. 51(5), 93 (2018)","journal-title":"ACM Comput. Surv."},{"key":"11_CR6","unstructured":"Doshi-Velez, F., Kim, B.: Towards a rigorous science of interpretable machine learning. arXiv preprint arXiv:1702.08608 (2017)"},{"issue":"3","key":"11_CR7","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1145\/3236386.3241340","volume":"16","author":"ZC Lipton","year":"2018","unstructured":"Lipton, Z.C.: The mythos of model interpretability. Queue 16(3), 30 (2018)","journal-title":"Queue"},{"key":"11_CR8","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.artint.2018.07.007","volume":"267","author":"T Miller","year":"2019","unstructured":"Miller, T.: Explanation in artificial intelligence: insights from the social sciences. Artif. Intell. 267, 1\u201338 (2019)","journal-title":"Artif. Intell."},{"key":"11_CR9","doi-asserted-by":"crossref","unstructured":"Abdul, A., Vermeulen, J., Wang, D., Lim, B.Y., Kankanhalli, M.: Trends and trajectories for explainable, accountable and intelligible systems: an HCI research agenda. In: Proceedings 2018 CHI Conference on Human Factors in Computing Systems, p. 582. ACM (2018)","DOI":"10.1145\/3173574.3174156"},{"key":"11_CR10","unstructured":"Biran, O., Cotton, C.: Explanation and justification in machine learning: a survey. In: IJCAI 2017 Workshop on Explainable AI (XAI), vol. 8, p. 1 (2017)"},{"issue":"2","key":"11_CR11","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1007\/s10462-005-4607-7","volume":"24","author":"F S\u00f8rmo","year":"2005","unstructured":"S\u00f8rmo, F., Cassens, J., Aamodt, A.: Explanation in case-based reasoning\u2013perspectives and goals. Artif. Intell. Rev. 24(2), 109\u2013143 (2005)","journal-title":"Artif. Intell. Rev."},{"key":"11_CR12","unstructured":"Johs, A.J., Lutts, M., Weber, R.O.: Measuring explanation quality in XCBR. In: Proceedings of ICCBR 2018, p. 75 (2018)"},{"key":"11_CR13","doi-asserted-by":"crossref","unstructured":"Tintarev, N., Masthoff, J.: A survey of explanations in recommender systems. In: 2007 IEEE 23rd International Conference on Data Engineering Workshop, pp. 801\u2013810. IEEE (2007)","DOI":"10.1109\/ICDEW.2007.4401070"},{"issue":"1","key":"11_CR14","doi-asserted-by":"publisher","first-page":"88","DOI":"10.2307\/2183532","volume":"74","author":"GH Harman","year":"1965","unstructured":"Harman, G.H.: The inference to the best explanation. Philos. Rev. 74(1), 88\u201395 (1965)","journal-title":"Philos. Rev."},{"key":"11_CR15","volume-title":"Scientific Explanation and the Causal Structure of the World","author":"WC Salmon","year":"1984","unstructured":"Salmon, W.C.: Scientific Explanation and the Causal Structure of the World. Princeton University Press, Princeton (1984)"},{"key":"11_CR16","doi-asserted-by":"publisher","DOI":"10.1093\/0198244274.001.0001","volume-title":"The Scientific Image","author":"BC Van Fraassen","year":"1980","unstructured":"Van Fraassen, B.C.: The Scientific Image. Oxford University Press, Oxford (1980)"},{"key":"11_CR17","doi-asserted-by":"publisher","first-page":"227","DOI":"10.1146\/annurev.psych.57.102904.190100","volume":"57","author":"FC Keil","year":"2006","unstructured":"Keil, F.C.: Explanation and understanding. Ann. Rev. Psychol. 57, 227\u2013254 (2006)","journal-title":"Ann. Rev. Psychol."},{"key":"11_CR18","unstructured":"Leake, D.B.: CBR in context: the present and future. In: Case-Based Reasoning: Experiences, Lessons, and Future Directions, pp. 3\u201330 (1996)"},{"issue":"2","key":"11_CR19","doi-asserted-by":"publisher","first-page":"103","DOI":"10.1007\/s10462-005-4606-8","volume":"24","author":"D Leake","year":"2005","unstructured":"Leake, D., McSherry, D.: Introduction to the special issue on explanation in case-based reasoning. Artif. Intell. Rev. 24(2), 103\u2013108 (2005)","journal-title":"Artif. Intell. Rev."},{"key":"11_CR20","unstructured":"Caruana, R., Kangarloo, H., Dionisio, J.D., Sinha, U., Johnson, D.: Case-based explanation of non-case-based learning methods. In: Proceedings of the AMIA Symposium, p. 212. American Medical Informatics Association (1999)"},{"key":"11_CR21","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 NIPs, pp. 1952\u20131960 (2014)"},{"key":"11_CR22","doi-asserted-by":"crossref","unstructured":"Pedreschi, D., Giannotti, F., Guidotti, R., Monreale, A., Ruggieri, S., Turini, F.: Meaningful explanations of Black Box AI decision systems. In: Proceedings of AAAI 2019 (2019)","DOI":"10.1609\/aaai.v33i01.33019780"},{"key":"11_CR23","unstructured":"Haykin, S.: Neural Networks, vol. 2. Prentice Hall, New York (1994)"},{"key":"11_CR24","unstructured":"Goodfellow, I., Bengio, Y., Courville, A.: Deep Learning. MIT Press, Cambridge (2016)"},{"key":"11_CR25","unstructured":"Kolodner, J.: Case Based Reasoning. Morgan Kaufmann, Burlington (2014)"},{"issue":"1","key":"11_CR26","doi-asserted-by":"crossref","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."},{"issue":"3","key":"11_CR27","doi-asserted-by":"publisher","first-page":"215","DOI":"10.1017\/S0269888906000646","volume":"20","author":"RL De Mantaras","year":"2006","unstructured":"De Mantaras, R.L., et al.: Retrieval, reuse, revise and retention in CBR. Knowl. Eng. Rev. 20(3), 215\u2013240 (2006)","journal-title":"Knowl. Eng. Rev."},{"issue":"4","key":"11_CR28","doi-asserted-by":"publisher","first-page":"4609","DOI":"10.1016\/j.eswa.2011.08.130","volume":"39","author":"S Sahin","year":"2012","unstructured":"Sahin, S., Tolun, M.R., Hassanpour, R.: Hybrid expert systems: a survey of current approaches and applications. Expert Syst. Appl. 39(4), 4609\u20134617 (2012)","journal-title":"Expert Syst. Appl."},{"key":"11_CR29","unstructured":"Negnevitsky, M.: Artificial Intelligence. Pearson Education, London (2005)"},{"key":"11_CR30","unstructured":"Medsker, L.R.: Hybrid Neural Network and Expert Systems. Springer, Heidelberg (2012)"},{"key":"11_CR31","unstructured":"Szegedy, C., et al.: Intriguing properties of neural networks. arXiv preprint arXiv:1312.6199 (2013)"},{"key":"11_CR32","unstructured":"Krizhevsky, A., Sutskever, I., Hinton, G.E.: Imagenet classification with deep convolutional neural networks. In: Advances in NIPs, pp. 1097\u20131105 (2012)"},{"key":"11_CR33","unstructured":"Witten, I.H., Frank, E., Hall, M.A., Pal, C.J.: Data Mining: Practical Machine Learning Tools and Techniques. Morgan Kaufmann, Burlington (2016)"},{"issue":"7553","key":"11_CR34","doi-asserted-by":"publisher","first-page":"436","DOI":"10.1038\/nature14539","volume":"521","author":"Y LeCun","year":"2015","unstructured":"LeCun, Y., Bengio, Y., Hinton, G.: Deep learning. Nature 521(7553), 436 (2015)","journal-title":"Nature"},{"issue":"1\u20132","key":"11_CR35","doi-asserted-by":"publisher","first-page":"135","DOI":"10.1016\/S0304-3800(02)00064-9","volume":"154","author":"JD Olden","year":"2002","unstructured":"Olden, J.D., Jackson, D.A.: Illuminating the \u201cblack box\u201d. Ecol. Model. 154(1\u20132), 135\u2013150 (2002)","journal-title":"Ecol. Model."},{"key":"11_CR36","doi-asserted-by":"crossref","unstructured":"Selvaraju, R.R., Cogswell, M., Das, A., Vedantam, R., Parikh, D., Batra, D.: Grad-CAM: visual explanations from deep networks via gradient-based localization. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 618\u2013626 (2017)","DOI":"10.1109\/ICCV.2017.74"},{"key":"11_CR37","unstructured":"Gilpin, L.H., Bau, D., Yuan, B.Z., Bajwa, A., Specter, M., Kagal, L.: Explaining explanations. arXiv preprint arXiv:1806.00069 (2018)"},{"key":"11_CR38","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"818","DOI":"10.1007\/978-3-319-10590-1_53","volume-title":"Computer Vision \u2013 ECCV 2014","author":"MD Zeiler","year":"2014","unstructured":"Zeiler, M.D., Fergus, R.: Visualizing and understanding convolutional networks. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014. LNCS, vol. 8689, pp. 818\u2013833. Springer, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-10590-1_53"},{"key":"11_CR39","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 770\u2013778 (2016)","DOI":"10.1109\/CVPR.2016.90"},{"issue":"3","key":"11_CR40","first-page":"1","volume":"1341","author":"D Erhan","year":"2009","unstructured":"Erhan, D., Bengio, Y., Courville, A., Vincent, P.: Visualizing higher-layer features of a deep network. Univ. Montreal 1341(3), 1 (2009)","journal-title":"Univ. Montreal"},{"key":"11_CR41","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1007\/3-540-58330-0_74","volume-title":"Topics in Case-Based Reasoning","author":"MT Keane","year":"1994","unstructured":"Keane, M.T.: Analogical asides on case-based reasoning. In: Wess, S., Althoff, K.-D., Richter, M.M. (eds.) EWCBR 1993. LNCS, vol. 837, pp. 21\u201332. Springer, Heidelberg (1994). https:\/\/doi.org\/10.1007\/3-540-58330-0_74"},{"issue":"3\u20135","key":"11_CR42","first-page":"393","volume":"27","author":"I Nunes","year":"2017","unstructured":"Nunes, I., Jannach, D.: A systematic review and taxonomy of explanations in decision support and recommender systems. UMUAI 27(3\u20135), 393\u2013444 (2017)","journal-title":"UMUAI"},{"key":"11_CR43","unstructured":"Becker, L., Jazayeri, K.: A connectionist approach to case-based reasoning. In: Proceedings of the Case-Based Reasoning Workshop, pp. 213\u2013217. Morgan Kaufmann (1989)"},{"key":"11_CR44","unstructured":"Thrift, P.: A neural network model for case-based reasoning. In: Proceedings of the Case-Based Reasoning Workshop, pp. 334\u2013337. Morgan Kaufmann (1989)"},{"key":"11_CR45","unstructured":"Hilario, M., Pellegrini, C., Alexandre, F.: Modular integration of connectionist and symbolic processing in knowledge-based systems. C.de R. en Informatique de Nancy (1994)"},{"issue":"2","key":"11_CR46","doi-asserted-by":"publisher","first-page":"145","DOI":"10.1016\/S0957-4174(98)00067-0","volume":"16","author":"CK Shin","year":"1999","unstructured":"Shin, C.K., Park, S.C.: Memory and neural network based expert system. Expert Syst. Appl. 16(2), 145\u2013155 (1999)","journal-title":"Expert Syst. Appl."},{"key":"11_CR47","doi-asserted-by":"publisher","first-page":"637","DOI":"10.1109\/72.846735","volume":"11","author":"CK Shin","year":"2000","unstructured":"Shin, C.K., Yun, U.T., Kim, H.K., Park, S.C.: A hybrid approach of neural network & memory-based learning to data mining. IEEE Trans. Neural Netw. 11, 637\u2013646 (2000)","journal-title":"IEEE Trans. Neural Netw."},{"key":"11_CR48","doi-asserted-by":"publisher","first-page":"4261","DOI":"10.1080\/00207540050205073","volume":"38","author":"CK Shin","year":"2000","unstructured":"Shin, C.K., Park, S.C.: A machine learning approach to yield management in semiconductor manufacturing. Int. J. Prod. Res. 38, 4261\u20134271 (2000)","journal-title":"Int. J. Prod. Res."},{"key":"11_CR49","unstructured":"Park, J.H., Shin, C.K., Im, K.H., Park, S.C.: A local weighting method to the integration of neural network and case based reasoning. In: Neural Networks for Signal Processing XI: Proceedings of the 2001 IEEE SPS Workshop, pp. 33\u201342. IEEE (2001)"},{"key":"11_CR50","doi-asserted-by":"publisher","first-page":"95","DOI":"10.1007\/978-1-4471-0687-6_5","volume-title":"Soft Computing in Case Based Reasoning","author":"Chung-Kwan Shin","year":"2001","unstructured":"Shin, C.K., Park, S.C.: Towards integration of memory based learning and neural networks. In: Pal, S.K., Dillon, T.S., Yeung, D.S. (eds.) Soft Computing in Case Based Reasoning, pp. 95\u2013114. Springer, London (2001). https:\/\/doi.org\/10.1007\/978-1-4471-0687-6_5"},{"issue":"3","key":"11_CR51","doi-asserted-by":"publisher","first-page":"265","DOI":"10.1023\/B:APIN.0000043559.83167.3d","volume":"21","author":"JH Park","year":"2004","unstructured":"Park, J.H., Im, K.H., Shin, C.K., Park, S.C.: MBNR: case-based reasoning with local feature weighting by neural network. Appl. Intell. 21(3), 265\u2013276 (2004)","journal-title":"Appl. Intell."},{"key":"11_CR52","doi-asserted-by":"publisher","first-page":"1012","DOI":"10.1007\/11816157_123","volume-title":"Lecture Notes in Computer Science","author":"Sang Chan Park","year":"2006","unstructured":"Park, S.C., Kim, J.W., Im, K.H.: Feature-weighted CBR with NN for symbolic features. In: Huang, D.S., Li, K., Irwin, G.W. (eds.) ICIC 2006. LNCS, vol. 4113, pp. 1012\u20131020. Springer, Heidelberg (2006). https:\/\/doi.org\/10.1007\/11816157_123"},{"issue":"1","key":"11_CR53","doi-asserted-by":"publisher","first-page":"77","DOI":"10.1016\/j.eswa.2005.11.020","volume":"32","author":"H Im","year":"2007","unstructured":"Im, H., Park, S.C.: Case-based reasoning and neural network based expert system for personalization. Expert Syst. Appl. 32(1), 77\u201385 (2007)","journal-title":"Expert Syst. Appl."},{"issue":"3","key":"11_CR54","doi-asserted-by":"publisher","first-page":"279","DOI":"10.1007\/s10489-007-0094-7","volume":"29","author":"S Ha","year":"2008","unstructured":"Ha, S.: A personalized counseling system using case-based reasoning with neural symbolic feature weighting (CANSY). Appl. Intell. 29(3), 279\u2013288 (2008)","journal-title":"Appl. Intell."},{"issue":"1","key":"11_CR55","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1016\/S0933-3657(96)00359-4","volume":"9","author":"EB Reategui","year":"1997","unstructured":"Reategui, E.B., Campbell, J.A., Leao, B.F.: Combining a neural network with case-based reasoning in a diagnostic system. Artif. Intell. Med. 9(1), 5\u201327 (1997)","journal-title":"Artif. Intell. Med."},{"issue":"3","key":"11_CR56","doi-asserted-by":"publisher","first-page":"387","DOI":"10.1016\/j.eswa.2003.09.009","volume":"26","author":"BS Yang","year":"2004","unstructured":"Yang, B.S., Han, T., Kim, Y.S.: Integration of ART-Kohonen NN and CBR for intelligent fault diagnosis. Expert Syst. Appl. 26(3), 387\u2013395 (2004)","journal-title":"Expert Syst. Appl."},{"key":"11_CR57","doi-asserted-by":"publisher","first-page":"176","DOI":"10.1007\/11925231_17","volume-title":"Lecture Notes in Computer Science","author":"Yanet Rodriguez","year":"2006","unstructured":"Rodriguez, Y., Garcia, M.M., De Baets, B., Morell, C., Bello, R.: A connectionist fuzzy case-based reasoning model. In: Gelbukh, A., Reyes-Garcia, C.A. (eds.) MICAI 2006. LNCS, vol. 4293, pp. 176\u2013185. Springer, Berlin (2006). https:\/\/doi.org\/10.1007\/11925231_17"},{"key":"11_CR58","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1007\/978-3-030-01081-2_2","volume-title":"Case-Based Reasoning Research and Development","author":"K Amin","year":"2018","unstructured":"Amin, K., Kapetanakis, S., Althoff, K.-D., Dengel, A., Petridis, M.: Answering with cases: a CBR approach to deep learning. In: Cox, M.T., Funk, P., Begum, S. (eds.) ICCBR 2018. LNCS (LNAI), vol. 11156, pp. 15\u201327. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-01081-2_2"},{"key":"11_CR59","doi-asserted-by":"crossref","unstructured":"Corchado, J.M., Rees, N., Lees, B., Aiken, J.: Data mining using example-based methods in oceanographic forecast models. In: IEE Colloquium on Knowledge Discovery and Data Mining (Digest No. 1998\/310), p. 7-1. IET (1998)","DOI":"10.1049\/ic:19980550"},{"issue":"2","key":"11_CR60","doi-asserted-by":"publisher","first-page":"105","DOI":"10.1080\/088395101750065723","volume":"15","author":"JM Corchado","year":"2001","unstructured":"Corchado, J.M., Lees, B.: A hybrid case-based model for forecasting. Appl. Artif. Intell. 15(2), 105\u2013127 (2001)","journal-title":"Appl. Artif. Intell."},{"key":"11_CR61","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"519","DOI":"10.1007\/3-540-46119-1_38","volume-title":"Advances in Case-Based Reasoning","author":"F Fdez-Riverola","year":"2002","unstructured":"Fdez-Riverola, F., Corchado, J.M., Torres, J.M.: An automated hybrid CBR system for forecasting. In: Craw, S., Preece, A. (eds.) ECCBR 2002. LNCS (LNAI), vol. 2416, pp. 519\u2013533. Springer, Heidelberg (2002). https:\/\/doi.org\/10.1007\/3-540-46119-1_38"},{"key":"11_CR62","unstructured":"Jothikimar, R., Shivakumar, N., Ramesh, P.S., Suganthan, Suresh, A.: Heart disease prediction system using ANN, RBF and CBR. Int. J. Pure Appl. Math. 117(21), 199\u2013217 (2017)"},{"issue":"9\u201310","key":"11_CR63","doi-asserted-by":"publisher","first-page":"2810","DOI":"10.1166\/jctn.2018.7543","volume":"15","author":"RR Kouser","year":"2018","unstructured":"Kouser, R.R., Manikandan, T., Kumar, V.V.: Heart disease prediction system using artificial neural network, radial basis function and case based reasoning. J. Comput. Theoret. Nanosci. 15(9\u201310), 2810\u20132817 (2018)","journal-title":"J. Comput. Theoret. Nanosci."},{"key":"11_CR64","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"625","DOI":"10.1007\/11536406_47","volume-title":"Case-Based Reasoning Research and Development","author":"R Weber","year":"2005","unstructured":"Weber, R., Proctor, Jason M., Waldstein, I., Kriete, A.: CBR for modeling complex systems. In: Mu\u00f1oz-\u00c1vila, H., Ricci, F. (eds.) ICCBR 2005. LNCS (LNAI), vol. 3620, pp. 625\u2013639. Springer, Heidelberg (2005). https:\/\/doi.org\/10.1007\/11536406_47"},{"key":"11_CR65","doi-asserted-by":"crossref","unstructured":"Peng, Y., Zhuang, L.: A case-based reasoning with feature weights derived by BP network. In: Intelligent Information Technology Application, pp. 26\u201329. IEEE (2007)","DOI":"10.1109\/IITA.2007.98"},{"key":"11_CR66","first-page":"57","volume":"9","author":"SK Biswas","year":"2014","unstructured":"Biswas, S.K., Sinha, N., Purakayastha, B., Marbaniang, L.: Hybrid expert system using case based reasoning and neural network for classification. Biol. Inspired Cogn. Archit. 9, 57\u201370 (2014)","journal-title":"Biol. Inspired Cogn. Archit."},{"issue":"4\u20136","key":"11_CR67","doi-asserted-by":"publisher","first-page":"272","DOI":"10.1504\/IJSTM.2015.073937","volume":"21","author":"SK Biswas","year":"2015","unstructured":"Biswas, S.K., Baruah, B., Sinha, N., Purkayastha, B.: A hybrid CBR classification model by integrating ANN into CBR. Int. J. Serv. Technol. Manag. 21(4\u20136), 272\u2013293 (2015)","journal-title":"Int. J. Serv. Technol. Manag."},{"issue":"24","key":"11_CR68","doi-asserted-by":"publisher","first-page":"7579","DOI":"10.1007\/s00500-016-2312-x","volume":"21","author":"SK Biswas","year":"2017","unstructured":"Biswas, S.K., Chakraborty, M., Singh, H.R., Devi, D., Purkayastha, B., Das, A.K.: Hybrid case-based reasoning system by cost-sensitive neural network for classification. Soft. Comput. 21(24), 7579\u20137596 (2017)","journal-title":"Soft. Comput."},{"issue":"2","key":"11_CR69","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1016\/S0933-3657(96)00367-3","volume":"9","author":"GF Cooper","year":"1997","unstructured":"Cooper, G.F., et al.: An evaluation of machine-learning methods for predicting pneumonia mortality. Artif. Intell. Med. 9(2), 107\u2013138 (1997)","journal-title":"Artif. Intell. Med."},{"key":"11_CR70","doi-asserted-by":"crossref","unstructured":"Caruana, R., Lou, Y., Gehrke, J., Koch, P., Sturm, M., Elhadad, N.: Intelligible models for healthcare: predicting pneumonia risk and hospital 30-day readmission. In: Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1721\u20131730. ACM (2015)","DOI":"10.1145\/2783258.2788613"},{"key":"11_CR71","unstructured":"Papernot, N., McDaniel, P.: Deep k-nearest neighbours: Towards confident, interpretable and robust deep learning. arXiv preprint arXiv:1803.04765 (2018)"},{"key":"11_CR72","doi-asserted-by":"crossref","unstructured":"Mittelstadt, B., Russell, C., Wachter, S.: Explaining explanations in AI. In: Proceedings of Conference on Fairness, Accountability, and Transparency (FAT*-19) (2019)","DOI":"10.1145\/3287560.3287574"},{"key":"11_CR73","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"122","DOI":"10.1007\/3-540-45006-8_12","volume-title":"Case-Based Reasoning Research and Development","author":"P Cunningham","year":"2003","unstructured":"Cunningham, P., Doyle, D., Loughrey, J.: An evaluation of the usefulness of case-based explanation. In: Ashley, K.D., Bridge, D.G. (eds.) ICCBR 2003. LNCS (LNAI), vol. 2689, pp. 122\u2013130. Springer, Heidelberg (2003). https:\/\/doi.org\/10.1007\/3-540-45006-8_12"},{"issue":"2","key":"11_CR74","doi-asserted-by":"publisher","first-page":"163","DOI":"10.1007\/s10462-005-4609-5","volume":"24","author":"C Nugent","year":"2005","unstructured":"Nugent, C., Cunningham, P.: A case-based explanation system for black-box systems. Artif. Intell. Rev. 24(2), 163\u2013178 (2005)","journal-title":"Artif. Intell. Rev."},{"key":"11_CR75","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"368","DOI":"10.1007\/11536406_29","volume-title":"Case-Based Reasoning Research and Development","author":"C Nugent","year":"2005","unstructured":"Nugent, C., Cunningham, P., Doyle, D.: The best way to instil confidence is by being right. In: Mu\u00f1oz-\u00c1vila, H., Ricci, F. (eds.) ICCBR 2005. LNCS (LNAI), vol. 3620, pp. 368\u2013381. Springer, Heidelberg (2005). https:\/\/doi.org\/10.1007\/11536406_29"},{"issue":"3","key":"11_CR76","doi-asserted-by":"publisher","first-page":"267","DOI":"10.1007\/s10844-008-0069-0","volume":"32","author":"C Nugent","year":"2009","unstructured":"Nugent, C., Doyle, D., Cunningham, P.: Gaining insight through case-based explanation. J. Intell. Inf. Syst. 32(3), 267\u2013295 (2009)","journal-title":"J. Intell. Inf. Syst."},{"key":"11_CR77","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"157","DOI":"10.1007\/978-3-540-28631-8_13","volume-title":"Advances in Case-Based Reasoning","author":"D Doyle","year":"2004","unstructured":"Doyle, D., Cunningham, P., Bridge, D., Rahman, Y.: Explanation oriented retrieval. In: Funk, P., Gonz\u00e1lez Calero, P.A. (eds.) ECCBR 2004. LNCS (LNAI), vol. 3155, pp. 157\u2013168. Springer, Heidelberg (2004). https:\/\/doi.org\/10.1007\/978-3-540-28631-8_13"},{"key":"11_CR78","doi-asserted-by":"publisher","first-page":"373","DOI":"10.1016\/0950-7051(96)81920-4","volume":"8","author":"R Andrews","year":"1995","unstructured":"Andrews, R., Diederich, J., Tickle, A.B.: Survey and critique of techniques for extracting rules from trained artificial neural networks. Knowl.-Based Syst. 8, 373\u2013389 (1995)","journal-title":"Knowl.-Based Syst."},{"key":"11_CR79","doi-asserted-by":"crossref","unstructured":"Ribeiro, M.T., Singh, S., Guestrin, C.: Why should I trust you?: explaining the predictions of any classifier. In: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1135\u20131144. ACM (2016)","DOI":"10.1145\/2939672.2939778"},{"issue":"2","key":"11_CR80","first-page":"87","volume":"6","author":"T Olsson","year":"2014","unstructured":"Olsson, T., Gillblad, D., Funk, P., Xiong, N.: Case-based reasoning for explaining probabilistic machine learning. Int. J. Comput. Sci. Inf. Technol. 6(2), 87\u2013101 (2014)","journal-title":"Int. J. Comput. Sci. Inf. Technol."},{"key":"11_CR81","unstructured":"Zharov, Y., Korzhenkov, D., Shvechikov, P., Tuzhilin, A.: YASENN: Explaining Neural Networks via Partitioning Activation Sequences. arXiv preprint arXiv:1811.02783 (2018)"},{"key":"11_CR82","unstructured":"Chen, C., Li, O., Barnett, A., Su, J., Rudin, C.: This looks like that: deep learning for interpretable image recognition. arXiv preprint arXiv:1806.10574 (2018)"},{"key":"11_CR83","doi-asserted-by":"crossref","unstructured":"Li, O., Liu, H., Chen, C., Rudin, C.: Deep learning for case-based reasoning through prototypes: a neural network that explains its predictions. In: Thirty-Second AAAI Conference on Artificial Intelligence. AAAI (2018)","DOI":"10.1609\/aaai.v32i1.11771"},{"key":"11_CR84","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"457","DOI":"10.1007\/978-3-319-46307-0_29","volume-title":"Discovery Science","author":"JR Zilke","year":"2016","unstructured":"Zilke, J.R., Loza Menc\u00eda, E., Janssen, F.: DeepRED \u2013 rule extraction from deep neural networks. In: Calders, T., Ceci, M., Malerba, D. (eds.) DS 2016. LNCS (LNAI), vol. 9956, pp. 457\u2013473. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46307-0_29"},{"issue":"7","key":"11_CR85","doi-asserted-by":"publisher","first-page":"e0130140","DOI":"10.1371\/journal.pone.0130140","volume":"10","author":"S Bach","year":"2015","unstructured":"Bach, S., Binder, A., Montavon, G., Klauschen, F., M\u00fcller, K.R., Samek, W.: On pixel-wise explanations for non-linear classifier decisions by layer-wise relevance propagation. PLoS ONE 10(7), e0130140 (2015)","journal-title":"PLoS ONE"},{"key":"11_CR86","unstructured":"Sundararajan, M., Taly, A., Yan, Q.: Axiomatic attribution for deep networks. In: Proceedings of the 34th International Conference on Machine Learning, vol. 70, pp. 3319\u20133328. JMLR. Org (2017)"},{"key":"11_CR87","unstructured":"Shrikumar, A., Greenside, P., Kundaje, A.: Learning important features through propagating activation differences. In: Proceedings of the 34th International Conference on Machine Learning, vol. 70, pp. 3145\u20133153. JMLR. Org (2017)"},{"key":"11_CR88","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"807","DOI":"10.1007\/978-3-319-77383-4_79","volume-title":"Advances in Multimedia Information Processing \u2013 PCM 2017","author":"C-L Zhang","year":"2018","unstructured":"Zhang, C.-L., Luo, J.-H., Wei, X.-S., Wu, J.: In defense of fully connected layers in visual representation transfer. In: Zeng, B., Huang, Q., El Saddik, A., Li, H., Jiang, S., Fan, X. (eds.) PCM 2017. LNCS, vol. 10736, pp. 807\u2013817. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-77383-4_79"},{"key":"11_CR89","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"144","DOI":"10.1007\/3-540-58330-0_83","volume-title":"Topics in Case-Based Reasoning","author":"P Myllym\u00e4ki","year":"1994","unstructured":"Myllym\u00e4ki, P., Tirri, H.: Massively parallel case-based reasoning with probabilistic similarity metrics. In: Wess, S., Althoff, K.-D., Richter, M.M. (eds.) EWCBR 1993. LNCS, vol. 837, pp. 144\u2013154. Springer, Heidelberg (1994). https:\/\/doi.org\/10.1007\/3-540-58330-0_83"},{"key":"11_CR90","unstructured":"Kofod-Petersen, A., Langseth, H., Aamodt, A.: Explanations in Bayesian networks using provenance through case-based reasoning. In: CBR Workshop Proceedings, p. 79 (2010)"},{"key":"11_CR91","doi-asserted-by":"crossref","unstructured":"Wallace, E., Feng, S., Boyd-Graber, J.: Interpreting Neural Networks with Nearest Neighbours. arXiv preprint arXiv:1809.02847 (2018)","DOI":"10.18653\/v1\/W18-5416"},{"key":"11_CR92","doi-asserted-by":"crossref","unstructured":"Card, D., Zhang, M., Smith, N.A.: Deep weighted averaging classifiers. In: Proceedings of Conference on Fairness, Accountability & Trust, pp. 369\u2013378. ACM, January 2019","DOI":"10.1145\/3287560.3287595"}],"container-title":["Lecture Notes in Computer Science","Case-Based Reasoning Research and Development"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-29249-2_11","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,13]],"date-time":"2024-03-13T17:35:33Z","timestamp":1710351333000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-29249-2_11"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030292485","9783030292492"],"references-count":92,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-29249-2_11","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"9 August 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICCBR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Case-Based Reasoning","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Otzenhausen","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Germany","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 September 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 September 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iccbr2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/iccbr2019.com\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"46","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"15","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"33% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Plus 1 meta review for borderline papers; 15 full papers were accepted for oral presentation and 11 for poster presentation; 13 subreviewers","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}