{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T00:58:18Z","timestamp":1743123498272,"version":"3.40.3"},"publisher-location":"Cham","reference-count":9,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031539657"},{"type":"electronic","value":"9783031539664"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-3-031-53966-4_17","type":"book-chapter","created":{"date-parts":[[2024,2,14]],"date-time":"2024-02-14T18:02:29Z","timestamp":1707933749000},"page":"222-236","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Evaluation of Selected Autoencoders in the Context of End-User Experience Management"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5222-954X","authenticated-orcid":false,"given":"Sven","family":"Beckmann","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7931-1105","authenticated-orcid":false,"given":"Bernhard","family":"Bauer","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,2,15]]},"reference":[{"key":"17_CR1","unstructured":"Bourne, V.: Digitale Eigensabotage und die Folgen f\u00fcr Unternehmen. https:\/\/www.nexthink.com\/wp-content\/uploads\/2021\/12\/Vanson-Bourne-Employee-Centric-Report_DE-1.pdf. Accessed 04 Apr 2023"},{"key":"17_CR2","doi-asserted-by":"publisher","unstructured":"Beckmann, S., Till, J., Bauer, B.: Endpoint-performance-monitoring for a better end-user experience. In: Proceedings of the 2022 European Symposium on Software Engineering, pp. 63\u201371 (2022). https:\/\/doi.org\/10.1145\/3571697.3571706","DOI":"10.1145\/3571697.3571706"},{"issue":"3","key":"17_CR3","doi-asserted-by":"publisher","first-page":"12","DOI":"10.1109\/MPRV.2018.03367731","volume":"17","author":"Y Meidan","year":"2018","unstructured":"Meidan, Y., et al.: N-baiot\u2014network-based detection of IoT botnet attacks using deep autoencoders. IEEE Pervasive Comput. 17(3), 12\u201322 (2018). https:\/\/doi.org\/10.1109\/MPRV.2018.03367731","journal-title":"IEEE Pervasive Comput."},{"key":"17_CR4","doi-asserted-by":"publisher","unstructured":"Borghesi, A., Bartolini, A., Lombardi, M., Milano, M., Benini, L.: Anomaly detection using autoencoders in high performance computing systems. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 33, no. 01, pp. 9428\u20139433 (2019). https:\/\/doi.org\/10.1609\/aaai.v33i01.33019428","DOI":"10.1609\/aaai.v33i01.33019428"},{"key":"17_CR5","doi-asserted-by":"crossref","unstructured":"Mirsky, Y., Doitshman, T., Elovici, Y., Shabtai, A.: Kitsune: an ensemble of autoencoders for online network intrusion detection. In: The Network and Distributed System Security Symposium (NDSS) (2018)","DOI":"10.14722\/ndss.2018.23204"},{"key":"17_CR6","unstructured":"Zong, B., et al.: Deep autoencoding Gaussian mixture model for unsupervised anomaly detection. In International conference on learning representations (2018)"},{"key":"17_CR7","unstructured":"Rocca, J.: Understanding Variational Autoencoders (VAEs). Building, step by step, the reasoning that leads to VAEs (2019). https:\/\/towardsdatascience.com\/understanding-variational-autoencoders-vaes-f70510919f73. Accessed 04 Apr 2023"},{"issue":"1","key":"17_CR8","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1214\/aoms\/1177729694","volume":"22","author":"S Kullback","year":"1951","unstructured":"Kullback, S., Leibler, R.A.: On information and sufficiency. Ann. Math. Stat. 22(1), 79\u201386 (1951)","journal-title":"Ann. Math. Stat."},{"key":"17_CR9","doi-asserted-by":"publisher","unstructured":"Bank, D., Koenigstein, N., Giryes, R.: Autoencoders. arXiv preprint arXiv:2003.05991. (2020). https:\/\/doi.org\/10.48550\/arXiv.2003.05991","DOI":"10.48550\/arXiv.2003.05991"}],"container-title":["Lecture Notes in Computer Science","Machine Learning, Optimization, and Data Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-53966-4_17","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,2,14]],"date-time":"2024-02-14T18:04:51Z","timestamp":1707933891000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-53966-4_17"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031539657","9783031539664"],"references-count":9,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-53966-4_17","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"15 February 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"LOD","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Machine Learning, Optimization, and Data Science","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Grasmere","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"United Kingdom","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 September 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 September 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"9","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"mod2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/lod2023.icas.cc\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"In-house system and EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"119","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":"72","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":"61% - 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":"5-6","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":"1-2","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)"}}]}}