{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,3]],"date-time":"2025-11-03T13:42:49Z","timestamp":1762177369766,"version":"3.40.3"},"publisher-location":"Cham","reference-count":20,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030658465"},{"type":"electronic","value":"9783030658472"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","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":[[2020]]},"DOI":"10.1007\/978-3-030-65847-2_4","type":"book-chapter","created":{"date-parts":[[2020,12,21]],"date-time":"2020-12-21T18:04:23Z","timestamp":1608573863000},"page":"35-45","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Evaluating Tree Explanation Methods for Anomaly Reasoning: A Case Study of SHAP TreeExplainer and TreeInterpreter"],"prefix":"10.1007","author":[{"given":"Pulkit","family":"Sharma","sequence":"first","affiliation":[]},{"given":"Shezan Rohinton","family":"Mirzan","sequence":"additional","affiliation":[]},{"given":"Apurva","family":"Bhandari","sequence":"additional","affiliation":[]},{"given":"Anish","family":"Pimpley","sequence":"additional","affiliation":[]},{"given":"Abhiram","family":"Eswaran","sequence":"additional","affiliation":[]},{"given":"Soundar","family":"Srinivasan","sequence":"additional","affiliation":[]},{"given":"Liqun","family":"Shao","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,12,22]]},"reference":[{"doi-asserted-by":"crossref","unstructured":"Caruana, R., Karampatziakis, N., Yessenalina, A.: An empirical evaluation of supervised learning in high dimensions. In: Proceedings of the 25th International Conference on Machine Learning, ICML 2008, pp. 96\u2013103 (2008)","key":"4_CR1","DOI":"10.1145\/1390156.1390169"},{"key":"4_CR2","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/1541880.1541882","volume":"41","author":"V Chandola","year":"2009","unstructured":"Chandola, V., Banerjee, A., Kumar, V.: Anomaly detection: a survey. ACM Comput. Surv. 41, 1\u201358 (2009)","journal-title":"ACM Comput. Surv."},{"doi-asserted-by":"crossref","unstructured":"Cuzzocrea, A., Mumolo, E., Cecolin, R.: Runtime anomaly detection in embedded systems by binary tracing and hidden Markov models. In 2015 IEEE 39th Annual Computer Software and Applications Conference, vol. 2, pp. 15\u201322 (2015)","key":"4_CR3","DOI":"10.1109\/COMPSAC.2015.89"},{"doi-asserted-by":"crossref","unstructured":"Duque Anton, S., Sinha, S., Schotten, H.: Anomaly-based intrusion detection in industrial data with SVM and random forests, pp. 1\u20136 (2019)","key":"4_CR4","DOI":"10.23919\/SOFTCOM.2019.8903672"},{"unstructured":"Gentzel, A., Garant, D., Jensen, D.: The case for evaluating causal models using interventional measures and empirical data. In: Wallach, H., Larochelle, H., Beygelzimer, A., d\u2019Alch\u00e9-Buc, F., Fox, E., Garnett, R. (eds.) Advances in Neural Information Processing Systems, vol. 32, pp. 11722\u201311732. Curran Associates Inc. (2019)","key":"4_CR5"},{"key":"4_CR6","volume-title":"Contributions to the Theory of Games","author":"HW Kuhn","year":"1953","unstructured":"Kuhn, H.W., Tucker, A.W.: Contributions to the Theory of Games, vol. 2. Princeton University Press, Princeton (1953)"},{"key":"4_CR7","doi-asserted-by":"publisher","first-page":"319","DOI":"10.1002\/asmb.446","volume":"17","author":"S Lipovetsky","year":"2001","unstructured":"Lipovetsky, S., Conklin, M.: Analysis of regression in game theory approach. Appl. Stochast. Models Bus. Ind. 17, 319\u2013330 (2001)","journal-title":"Appl. Stochast. Models Bus. Ind."},{"issue":"1","key":"4_CR8","doi-asserted-by":"publisher","first-page":"2522","DOI":"10.1038\/s42256-019-0138-9","volume":"2","author":"SM Lundberg","year":"2020","unstructured":"Lundberg, S.M., et al.: From local explanations to global understanding with explainable AI for trees. Nat. Mach. Intell. 2(1), 2522\u20135839 (2020)","journal-title":"Nat. Mach. Intell."},{"unstructured":"Lundberg, S.M., Lee, S.-I.: A unified approach to interpreting model predictions. In: Advances in Neural Information Processing Systems, vol. 30 (2017)","key":"4_CR9"},{"doi-asserted-by":"crossref","unstructured":"Peiris, M., Hill, J.H., Thelin, J., Bykov, S., Kliot, G., Konig, C.: PAD: performance anomaly detection in multi-server distributed systems. In: 2014 IEEE 7th International Conference on Cloud Computing, pp. 769\u2013776 (2014)","key":"4_CR10","DOI":"10.1109\/CLOUD.2014.107"},{"doi-asserted-by":"crossref","unstructured":"Primartha, R., Tama, B.A.: Anomaly detection using random forest: a performance revisited. In: 2017 International Conference on Data and Software Engineering (ICoDSE), pp. 1\u20136 (2017)","key":"4_CR11","DOI":"10.1109\/ICODSE.2017.8285847"},{"doi-asserted-by":"crossref","unstructured":"Ribeiro, M.T., Singh, S., Guestrin, C.: \u201cwhy should I trust you?\u201d: explaining the predictions of any classifier. In: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Francisco, CA, USA, 13\u201317 August 2016, pp. 1135\u20131144 (2016)","key":"4_CR12","DOI":"10.1145\/2939672.2939778"},{"unstructured":"Saabas, A.: Treeinterpreter. https:\/\/github.com\/andosa\/treeinterpreter","key":"4_CR13"},{"doi-asserted-by":"crossref","unstructured":"Shao, L., et al.: Griffon. In: Proceedings of the ACM Symposium on Cloud Computing - SoCC 2019 (2019)","key":"4_CR14","DOI":"10.1145\/3357223.3362716"},{"unstructured":"Shrikumar, A., Greenside, P., Kundaje, A.: Learning important features through propagating activation differences. CoRR abs\/1704.02685 (2017)","key":"4_CR15"},{"unstructured":"Shrikumar, A., Greenside, P., Shcherbina, A., Kundaje, A.: Not just a black box: learning important features through propagating activation differences. CoRR abs\/1605.01713 (2016)","key":"4_CR16"},{"key":"4_CR17","doi-asserted-by":"publisher","first-page":"647","DOI":"10.1007\/s10115-013-0679-x","volume":"41","author":"E \u0160trumbelj","year":"2013","unstructured":"\u0160trumbelj, E., Kononenko, I.: Explaining prediction models and individual predictions with feature contributions. Knowl. Inf. Syst. 41, 647\u2013665 (2013)","journal-title":"Knowl. Inf. Syst."},{"doi-asserted-by":"crossref","unstructured":"Sultani, W., Chen, C., Shah, M.: Real-world anomaly detection in surveillance videos. In: The IEEE Conference on Computer Vision and Pattern Recognition (2018)","key":"4_CR18","DOI":"10.1109\/CVPR.2018.00678"},{"key":"4_CR19","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1145\/1852102.1852106","volume":"28","author":"W Webber","year":"2010","unstructured":"Webber, W., Moffat, A., Zobel, J.: A similarity measure for indefinite rankings. ACM Trans. Inf. Syst. 28, 4 (2010)","journal-title":"ACM Trans. Inf. Syst."},{"doi-asserted-by":"crossref","unstructured":"Wulsin, D., Blanco, J., Mani, R., Litt, B.: Semi-supervised anomaly detection for EEG waveforms using deep belief nets. In: 2010 Ninth International Conference on Machine Learning and Applications, pp. 436\u2013441 (2010)","key":"4_CR20","DOI":"10.1109\/ICMLA.2010.71"}],"container-title":["Lecture Notes in Computer Science","Advances in Conceptual Modeling"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-65847-2_4","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,8]],"date-time":"2022-12-08T05:53:00Z","timestamp":1670478780000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-65847-2_4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030658465","9783030658472"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-65847-2_4","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"22 December 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ER","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Conceptual Modeling","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Vienna","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Austria","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3 November 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6 November 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"39","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"er2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/er2020.big.tuwien.ac.at\/","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":"143","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":"28","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":"16","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":"20% - 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 held virtually.","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)"}}]}}