{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,22]],"date-time":"2025-11-22T11:27:44Z","timestamp":1763810864875,"version":"3.40.3"},"publisher-location":"Cham","reference-count":22,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783031134470"},{"type":"electronic","value":"9783031134487"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-13448-7_14","type":"book-chapter","created":{"date-parts":[[2022,8,22]],"date-time":"2022-08-22T23:03:22Z","timestamp":1661209402000},"page":"168-180","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Representation and\u00a0Interpretability of\u00a0IE Integral Neural Networks"],"prefix":"10.1007","author":[{"given":"Aoi","family":"Honda","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yudai","family":"Kamata","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Simon","family":"James","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,8,23]]},"reference":[{"key":"14_CR1","unstructured":"Abadi, M., et al.: Tensorflow: a system for large-scale machine learning. In: 12th USENIX Symposium on Operating Systems Design and Implementation (OSDI 2016), pp. 265\u2013283 (2016)"},{"key":"14_CR2","doi-asserted-by":"publisher","first-page":"82","DOI":"10.1016\/j.inffus.2019.12.012","volume":"58","author":"AB Arrieta","year":"2020","unstructured":"Arrieta, A.B., et al.: Explainable artificial intelligence (XAI): concepts, taxonomies, opportunities and challenges toward responsible AI. Inf. Fusion 58, 82\u2013115 (2020)","journal-title":"Inf. Fusion"},{"key":"14_CR3","series-title":"Studies in Fuzziness and Soft Computing","doi-asserted-by":"publisher","first-page":"205","DOI":"10.1007\/978-3-030-15305-2_8","volume-title":"Discrete Fuzzy Measures","author":"G Beliakov","year":"2020","unstructured":"Beliakov, G., James, S., Wu, J.-Z.: Learning fuzzy measures. In: Discrete Fuzzy Measures. SFSC, vol. 382, pp. 205\u2013239. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-15305-2_8"},{"key":"14_CR4","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1038\/538020a","volume":"538","author":"D Castelvecchi","year":"2016","unstructured":"Castelvecchi, D.: The black box of AI. Nature 538, 20\u201323 (2016)","journal-title":"Nature"},{"key":"14_CR5","unstructured":"Chollet, F., et al. Keras. GitHub (2015). https:\/\/github.com\/fchollet\/keras"},{"key":"14_CR6","doi-asserted-by":"publisher","first-page":"131","DOI":"10.5802\/aif.53","volume":"5","author":"G Choquet","year":"1953","unstructured":"Choquet, G.: A value for n-person games. Ann. Inst. Fourier 5, 131\u2013295 (1953)","journal-title":"Ann. Inst. Fourier"},{"key":"14_CR7","doi-asserted-by":"publisher","unstructured":"Cutaways, V., Stock, T.: Interaction. Auto. Tech. Review. 5(3), 4\u201311 (2016). https:\/\/doi.org\/10.1365\/s40112-016-1097-8","DOI":"10.1365\/s40112-016-1097-8"},{"issue":"101994","key":"14_CR8","first-page":"1","volume":"57","author":"YK Dwivedi","year":"2021","unstructured":"Dwivedi, Y.K., et al.: Artificial intelligence (AI): multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. Int. J. Inf. Manag. 57(101994), 1\u201347 (2021)","journal-title":"Int. J. Inf. Manag."},{"key":"14_CR9","volume-title":"Set Functions","author":"M Grabisch","year":"2016","unstructured":"Grabisch, M.: Set Functions. Games and Capacities in Decision Making. Springer, Berlin, New York (2016)"},{"key":"14_CR10","unstructured":"Domingos, P., Poon, H.: Sum-product networks: a new deep architecture. In: Proceedings of the 12th Conference on Uncertainty in Artificial Intelligence (UAI), pp. 337\u2013346 (2012)"},{"key":"14_CR11","doi-asserted-by":"crossref","unstructured":"Harrison, D., Rubinfeld, D.L.: Hedonic prices and the demand for clean air. J. Environ. Economics and Management 5, 81\u2013102 (1993)","DOI":"10.1016\/0095-0696(78)90006-2"},{"key":"14_CR12","unstructured":"Honda, A., Itabashi, M., James, S.: A neural network based on the inclusion-exclusion integral and its application to data analysis. preprint (2021)"},{"key":"14_CR13","doi-asserted-by":"publisher","first-page":"28","DOI":"10.1016\/j.inffus.2019.10.004","volume":"56","author":"A Honda","year":"2020","unstructured":"Honda, A., James, S.: Parameter learning and applications of the inclusion-exclusion integral for data fusion and analysis. Inf. Fusion 56, 28\u201338 (2020)","journal-title":"Inf. Fusion"},{"key":"14_CR14","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1007\/978-3-319-67422-3_6","volume-title":"Modeling Decisions for Artificial Intelligence","author":"A Honda","year":"2017","unstructured":"Honda, A., James, S., Rajasegarar, S.: Orness and Cardinality Indices for Averaging Inclusion-Exclusion Integrals. In: Torra, V., Narukawa, Y., Honda, A., Inoue, S. (eds.) MDAI 2017. LNCS (LNAI), vol. 10571, pp. 51\u201362. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-67422-3_6"},{"key":"14_CR15","series-title":"Communications in Computer and Information Science","doi-asserted-by":"publisher","first-page":"480","DOI":"10.1007\/978-3-642-14055-6_50","volume-title":"Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Methods","author":"A Honda","year":"2010","unstructured":"Honda, A., Okamoto, J.: Inclusion-exclusion integral and its application to subjective video quality estimation. In: H\u00fcllermeier, E., Kruse, R., Hoffmann, F. (eds.) IPMU 2010. CCIS, vol. 80, pp. 480\u2013489. Springer, Heidelberg (2010). https:\/\/doi.org\/10.1007\/978-3-642-14055-6_50"},{"key":"14_CR16","doi-asserted-by":"publisher","first-page":"136","DOI":"10.1016\/j.ins.2016.09.063","volume":"376","author":"A Honda","year":"2017","unstructured":"Honda, A., Okazaki, Y.: Theory of inclusion-exclusion integral. Inf. Sci. 376, 136\u2013147 (2017)","journal-title":"Inf. Sci."},{"issue":"7","key":"14_CR17","doi-asserted-by":"publisher","first-page":"1291","DOI":"10.1109\/TFUZZ.2019.2917124","volume":"28","author":"MA Islam","year":"2020","unstructured":"Islam, M.A., Anderson, D.T., Pinar, A.J., Havens, T.C., Scott, G., Keller, J.M.: Enabling explainable fusion in deep learning with fuzzy integral neural networks. IEEE Trans. Fuzzy Syst. 28(7), 1291\u20131300 (2020)","journal-title":"IEEE Trans. Fuzzy Syst."},{"key":"14_CR18","series-title":"Studies in Computational Intelligence","doi-asserted-by":"publisher","first-page":"111","DOI":"10.1007\/978-3-642-32378-2_8","volume-title":"Computational Intelligence in Intelligent Data Analysis","author":"C Otte","year":"2013","unstructured":"Otte, C.: Safe and interpretable machine learning: a methodological review. In: Moewes, C., Nunberger, A. (eds.) Computational Intelligence in Intelligent Data Analysis. Studies in Computational Intelligence, vol. 445, pp. 111\u2013122. Springer, Heidelberg (2013). https:\/\/doi.org\/10.1007\/978-3-642-32378-2_8"},{"key":"14_CR19","unstructured":"Ross, C., Swetlitz, I.: IBM\u2019s Watson supercomputer recommended \u2018unsafe and incorrect\u2019 cancer treatments, internal documents show. STAT+, 25 July 2018. https:\/\/www.statnews.com\/2018\/07\/25\/ibm-watson-recommended-unsafe-incorrect-treatments\/"},{"key":"14_CR20","unstructured":"Samek, W., Wiegand, T., M\u00fcller, K.-R.: Explainable artificial intelligence: understanding, visualizing and interpreting deep learning models. ITU Journal: ICT Discoveries - Special Issue 1 - The Impact of Artificial Intelligence (AI). Commun. Netw. Serv. 1, 1\u201310 (2017)"},{"key":"14_CR21","doi-asserted-by":"crossref","first-page":"169","DOI":"10.5486\/PMD.1961.8.1-2.16","volume":"8","author":"B Schweizer","year":"1961","unstructured":"Schweizer, B., Sklar, A.: Associative functions and statistical triangle inequalities. Publ. Math. Debrecen 8, 169\u2013186 (1961)","journal-title":"Publ. Math. Debrecen"},{"key":"14_CR22","doi-asserted-by":"crossref","unstructured":"Shapley, L.S.: Theory of capacities. In: Contributions to the Theory Games (AM-28), II, pp. 307\u2013318 (1953)","DOI":"10.1515\/9781400881970-018"}],"container-title":["Lecture Notes in Computer Science","Modeling Decisions for Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-13448-7_14","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,2,15]],"date-time":"2023-02-15T16:03:09Z","timestamp":1676476989000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-13448-7_14"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031134470","9783031134487"],"references-count":22,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-13448-7_14","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"23 August 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"MDAI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Modeling Decisions for Artificial Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Sant Cugat","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Spain","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"30 August 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2 September 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"mdai2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/mdai.cat\/mdai2022\/","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":"None","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"41","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":"16","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":"39% - 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)"}}]}}