{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T22:23:12Z","timestamp":1743114192754,"version":"3.40.3"},"publisher-location":"Cham","reference-count":25,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030975456"},{"type":"electronic","value":"9783030975463"}],"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\/978-3-030-97546-3_3","type":"book-chapter","created":{"date-parts":[[2022,3,18]],"date-time":"2022-03-18T04:41:28Z","timestamp":1647578488000},"page":"27-39","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["HESIP: A Hybrid System for\u00a0Explaining Sub-symbolic Predictions"],"prefix":"10.1007","author":[{"given":"Abdus","family":"Salam","sequence":"first","affiliation":[]},{"given":"Rolf","family":"Schwitter","sequence":"additional","affiliation":[]},{"given":"Mehmet A.","family":"Orgun","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,3,19]]},"reference":[{"issue":"2","key":"3_CR1","doi-asserted-by":"publisher","first-page":"169","DOI":"10.1017\/S1471068413000689","volume":"15","author":"E Bellodi","year":"2015","unstructured":"Bellodi, E., Riguzzi, F.: Structure learning of probabilistic logic programs by searching the clause space. Theory Pract. Logic Program. 15(2), 169\u2013212 (2015)","journal-title":"Theory Pract. Logic Program."},{"issue":"4","key":"3_CR2","doi-asserted-by":"publisher","first-page":"834","DOI":"10.1109\/TPAMI.2017.2699184","volume":"40","author":"LC Chen","year":"2017","unstructured":"Chen, L.C., Papandreou, G., Kokkinos, I., Murphy, K., Yuille, A.L.: DeepLab: semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected CRFs. IEEE Trans. PAMI 40(4), 834\u2013848 (2017)","journal-title":"IEEE Trans. PAMI"},{"key":"3_CR3","doi-asserted-by":"crossref","unstructured":"Chen, X., Mottaghi, R., Liu, X., Fidler, S., Urtasun, R., Yuille, A.: Detect what you can: detecting and representing objects using holistic models and body parts. In: Proceedings of CVPR 2014, pp. 1971\u20131978 (2014)","DOI":"10.1109\/CVPR.2014.254"},{"key":"3_CR4","unstructured":"De Raedt, L., Manhaeve, R., Dumancic, S., Demeester, T., Kimmig, A.: Neuro-symbolic = neural + logical + probabilistic. In: NeSy\u201919@ IJCAI, the 14th International Workshop on Neural-Symbolic Learning and Reasoning (2019)"},{"issue":"1","key":"3_CR5","first-page":"1","volume":"14","author":"M Genesereth","year":"2020","unstructured":"Genesereth, M., Chaudhri, V.K.: Introduction to logic programming. Synth. Lect. Artif. Intell. Mach. Learn. 14(1), 1\u2013219 (2020)","journal-title":"Synth. Lect. Artif. Intell. Mach. Learn."},{"key":"3_CR6","doi-asserted-by":"crossref","unstructured":"He, K., Gkioxari, G., Doll\u00e1r, P., Girshick, R.: Mask R-CNN. In: 2017 IEEE International Conference on Computer Vision (ICCV), pp. 2980\u20132988 (2017)","DOI":"10.1109\/ICCV.2017.322"},{"key":"3_CR7","unstructured":"Ilkou, E., Koutraki, M.: Symbolic vs sub-symbolic AI methods: friends or enemies? In: CIKM (Workshops) (2020)"},{"key":"3_CR8","unstructured":"Kautz, H.: The Third AI Summer, AAAI Robert S. Engelmore Memorial Lecture. AAAI 2020 (2020). https:\/\/www.cs.rochester.edu\/u\/kautz\/talks\/Kautz Engelmore Lecture Directors Cut.pdf. Accessed 17 July 2021"},{"key":"3_CR9","unstructured":"Krizhevsky, A., Sutskever, I., Hinton, G.E.: Imagenet classification with deep convolutional neural networks. In: NIPS 2012, pp. 1097\u20131105 (2012)"},{"issue":"7553","key":"3_CR10","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"},{"key":"3_CR11","unstructured":"Lipton, Z.C.: The mythos of model interpretability. arXiv preprint arXiv:1606.03490 (2016)"},{"issue":"4","key":"3_CR12","doi-asserted-by":"publisher","first-page":"295","DOI":"10.1007\/BF03037089","volume":"8","author":"S Muggleton","year":"1991","unstructured":"Muggleton, S.: Inductive logic programming. New Gener. Comput. 8(4), 295\u2013318 (1991)","journal-title":"New Gener. Comput."},{"key":"3_CR13","series-title":"Communications in Computer and Information Science","doi-asserted-by":"publisher","first-page":"180","DOI":"10.1007\/978-3-030-43823-4_16","volume-title":"Machine Learning and Knowledge Discovery in Databases","author":"J Rabold","year":"2020","unstructured":"Rabold, J., Deininger, H., Siebers, M., Schmid, U.: Enriching visual with verbal explanations for relational concepts \u2013 combining LIME with aleph. In: Cellier, P., Driessens, K. (eds.) ECML PKDD 2019. CCIS, vol. 1167, pp. 180\u2013192. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-43823-4_16"},{"issue":"6","key":"3_CR14","doi-asserted-by":"publisher","first-page":"1137","DOI":"10.1109\/TPAMI.2016.2577031","volume":"39","author":"S Ren","year":"2016","unstructured":"Ren, S., He, K., Girshick, R., Sun, J.: Faster R-CNN: towards real-time object detection with region proposal networks. IEEE Trans. PAMI 39(6), 1137\u20131149 (2016)","journal-title":"IEEE Trans. PAMI"},{"key":"3_CR15","doi-asserted-by":"crossref","unstructured":"Ribeiro, M.T., Singh, S., Guestrin, C.: Why should I trust you?: explaining the predictions of any classifier. In: ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1135\u20131144. ACM (2016)","DOI":"10.1145\/2939672.2939778"},{"key":"3_CR16","doi-asserted-by":"crossref","unstructured":"Ribeiro, M.T., Singh, S., Guestrin, C.: Anchors: high-precision model-agnostic explanations. In: AAAI 2018, vol. 32, no. 1, April 2018","DOI":"10.1609\/aaai.v32i1.11491"},{"key":"3_CR17","unstructured":"Riguzzi, F., Azzolini, D.: cplint Manual. SWI-Prolog Version (2020). http:\/\/friguzzi.github.io\/cplint\/_build\/latex\/cplint.pdf. Accessed 17 July 2021"},{"key":"3_CR18","volume-title":"Artificial Intelligence: A Modern Approach","author":"S Russell","year":"2020","unstructured":"Russell, S., Norvig, P.: Artificial Intelligence: A Modern Approach. Pearson, London (2020)"},{"key":"3_CR19","unstructured":"Salam, A., Schwitter, R., Orgun, M.A.: Human-understandable and machine-processable explanations for sub-symbolic predictions. In: International Workshop on Controlled Natural Language (2021)"},{"key":"3_CR20","doi-asserted-by":"crossref","unstructured":"Schwitter, R.: Lossless semantic round-tripping in PENG$$^{ASP}$$. In: IJCAI 2020. Demonstrations Track, Yokohama, Japan, pp. 5291\u20135293 (2020)","DOI":"10.24963\/ijcai.2020\/773"},{"issue":"1","key":"3_CR21","doi-asserted-by":"publisher","first-page":"35","DOI":"10.1007\/s13218-018-0565-5","volume":"33","author":"M Siebers","year":"2018","unstructured":"Siebers, M., Schmid, U.: Please delete that! Why should I? KI - K\u00fcnstliche Intelligenz 33(1), 35\u201344 (2018). https:\/\/doi.org\/10.1007\/s13218-018-0565-5","journal-title":"KI - K\u00fcnstliche Intelligenz"},{"key":"3_CR22","unstructured":"Srinivasan, A.: The Aleph Manual (2007). http:\/\/www.cs.ox.ac.uk\/activities\/programinduction\/Aleph\/aleph.html. Accessed 17 July 2021"},{"key":"3_CR23","unstructured":"Wu, Y., Kirillov, A., Massa, F., Lo, W.Y., Girshick, R.: Detectron2 (2019). https:\/\/github.com\/facebookresearch\/detectron2. Accessed 17 July 2021"},{"key":"3_CR24","unstructured":"Zhang, X., Zhao, J., LeCun, Y.: Character-level convolutional networks for text classification. In: NIPS 2015, pp. 649\u2013657 (2015)"},{"key":"3_CR25","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2020.2981333","author":"Z Zhang","year":"2020","unstructured":"Zhang, Z., Cui, P., Zhu, W.: Deep learning on graphs: a survey. IEEE Trans. KDE (2020). https:\/\/doi.org\/10.1109\/TKDE.2020.2981333","journal-title":"IEEE Trans. KDE"}],"container-title":["Lecture Notes in Computer Science","AI 2021: Advances in Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-97546-3_3","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,29]],"date-time":"2023-01-29T12:14:27Z","timestamp":1674994467000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-97546-3_3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783030975456","9783030975463"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-97546-3_3","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":"19 March 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"AI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Australasian Joint Conference on Artificial Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Sydney, NSW","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Australia","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":"2 February 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 February 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"34","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ausai2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/ajcai2021.net","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":"120","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":"64","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":"53% - 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":"5","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":"The conference was postponed to 2022 and held virtually due to the COVID-19 pandemic.","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)"}}]}}