{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,19]],"date-time":"2025-12-19T15:46:23Z","timestamp":1766159183971,"version":"3.40.3"},"publisher-location":"Cham","reference-count":23,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031372483"},{"type":"electronic","value":"9783031372490"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"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":[[2023]]},"DOI":"10.1007\/978-3-031-37249-0_7","type":"book-chapter","created":{"date-parts":[[2023,7,14]],"date-time":"2023-07-14T04:02:11Z","timestamp":1689307331000},"page":"85-99","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Improving Recommender System Diversity with\u00a0Variational Autoencoders"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0562-343X","authenticated-orcid":false,"given":"Sheetal","family":"Borar","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2046-1299","authenticated-orcid":false,"given":"Hilde","family":"Weerts","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2656-2055","authenticated-orcid":false,"given":"Binyam","family":"Gebre","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4955-0743","authenticated-orcid":false,"given":"Mykola","family":"Pechenizkiy","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,7,15]]},"reference":[{"issue":"5","key":"7_CR1","doi-asserted-by":"publisher","first-page":"896","DOI":"10.1109\/TKDE.2011.15","volume":"24","author":"G Adomavicius","year":"2012","unstructured":"Adomavicius, G., Kwon, Y.: Improving aggregate recommendation diversity using ranking-based techniques. IEEE Trans. Knowl. Data Eng. 24(5), 896\u2013911 (2012). https:\/\/doi.org\/10.1109\/TKDE.2011.15","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"7_CR2","unstructured":"Anderson, C.: The long tail (2004). https:\/\/www.wired.com\/2004\/10\/tail\/"},{"issue":"1","key":"7_CR3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10844-013-0252-9","volume":"42","author":"T Aytekin","year":"2014","unstructured":"Aytekin, T., Karakaya, M.\u00d6.: Clustering-based diversity improvement in top-n recommendation. J. Intell. Inf. Syst. 42(1), 1\u201318 (2014)","journal-title":"J. Intell. Inf. Syst."},{"key":"7_CR4","unstructured":"Bradley, K., Smyth, B.: Improving recommendation diversity (2001)"},{"key":"7_CR5","doi-asserted-by":"publisher","unstructured":"Carbonell, J., Goldstein, J.: The use of MMR, diversity-based reranking for reordering documents and producing summaries. In: Proceedings of the 21st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 335\u2013336. SIGIR 1998, Association for Computing Machinery, New York, NY, USA (1998). https:\/\/doi.org\/10.1145\/290941.291025. https:\/\/doi-org.libproxy.aalto.fi\/10.1145\/290941.291025","DOI":"10.1145\/290941.291025"},{"key":"7_CR6","doi-asserted-by":"publisher","unstructured":"Chaney, A.J.B., Stewart, B.M., Engelhardt, B.E.: How algorithmic confounding in recommendation systems increases homogeneity and decreases utility. In: Proceedings of the 12th ACM Conference on Recommender Systems. ACM (2018). https:\/\/doi.org\/10.1145\/3240323.3240370","DOI":"10.1145\/3240323.3240370"},{"key":"7_CR7","doi-asserted-by":"publisher","unstructured":"Dacrema, M.F., Cremonesi, P., Jannach, D.: Are we really making much progress? a worrying analysis of recent neural recommendation approaches. In: Proceedings of the 13th ACM Conference on Recommender Systems. ACM (2019). https:\/\/doi.org\/10.1145\/3298689.3347058","DOI":"10.1145\/3298689.3347058"},{"key":"7_CR8","doi-asserted-by":"crossref","unstructured":"Guo, W., Krauth, K., Jordan, M.I., Garg, N.: The stereotyping problem in collaboratively filtered recommender systems (2021)","DOI":"10.1145\/3465416.3483298"},{"key":"7_CR9","doi-asserted-by":"publisher","unstructured":"Harper, F.M., Konstan, J.A.: The MovieLens datasets: History and context. ACM Trans. Interact. Intell. Syst. 5(4), 2827872 (2015). https:\/\/doi.org\/10.1145\/2827872","DOI":"10.1145\/2827872"},{"key":"7_CR10","doi-asserted-by":"crossref","unstructured":"Jain, U., Zhang, Z., Schwing, A.G.: Creativity: generating diverse questions using variational autoencoders. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2017)","DOI":"10.1109\/CVPR.2017.575"},{"issue":"4","key":"7_CR11","doi-asserted-by":"publisher","first-page":"422","DOI":"10.1145\/582415.582418","volume":"20","author":"K J\u00e4rvelin","year":"2002","unstructured":"J\u00e4rvelin, K., Kek\u00e4l\u00e4inen, J.: Cumulated gain-based evaluation of IR techniques. ACM Trans. Inf. Syst.(TOIS) 20(4), 422\u2013446 (2002)","journal-title":"ACM Trans. Inf. Syst.(TOIS)"},{"key":"7_CR12","doi-asserted-by":"publisher","unstructured":"Kingma, D.P., Welling, M.: An introduction to variational autoencoders. Found. Trends\u00ae Mach. Learn. 12(4), 307\u2013392 (2019). https:\/\/doi.org\/10.1561\/2200000056","DOI":"10.1561\/2200000056"},{"issue":"4","key":"7_CR13","doi-asserted-by":"publisher","first-page":"441","DOI":"10.1007\/s11257-011-9118-4","volume":"22","author":"BP Knijnenburg","year":"2012","unstructured":"Knijnenburg, B.P., Willemsen, M.C., Gantner, Z., Soncu, H., Newell, C.: Explaining the user experience of recommender systems. User Model. User-Adap. Inter. 22(4), 441\u2013504 (2012)","journal-title":"User Model. User-Adap. Inter."},{"key":"7_CR14","doi-asserted-by":"publisher","first-page":"154","DOI":"10.1016\/j.knosys.2017.02.009","volume":"123","author":"M Kunaver","year":"2017","unstructured":"Kunaver, M., Po\u017erl, T.: Diversity in recommender systems-a survey. Knowl.-Based Syst. 123, 154\u2013162 (2017)","journal-title":"Knowl.-Based Syst."},{"key":"7_CR15","doi-asserted-by":"publisher","unstructured":"Lathia, N., Hailes, S., Capra, L., Amatriain, X.: Temporal diversity in recommender systems. In: Proceedings of the 33rd International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 210\u2013217. SIGIR 2010, Association for Computing Machinery, New York, NY, USA (2010). https:\/\/doi.org\/10.1145\/1835449.1835486","DOI":"10.1145\/1835449.1835486"},{"key":"7_CR16","doi-asserted-by":"crossref","unstructured":"Liang, D., Krishnan, R.G., Hoffman, M.D., Jebara, T.: Variational autoencoders for collaborative filtering (2018)","DOI":"10.1145\/3178876.3186150"},{"key":"7_CR17","doi-asserted-by":"publisher","unstructured":"Liu, J.G., Shi, K., Guo, Q.: Solving the accuracy-diversity dilemma via directed random walks. Phys. Rev. E 85(1), 016118 (2012). https:\/\/doi.org\/10.1103\/physreve.85.016118","DOI":"10.1103\/physreve.85.016118"},{"key":"7_CR18","doi-asserted-by":"publisher","unstructured":"Mansoury, M., Abdollahpouri, H., Pechenizkiy, M., Mobasher, B., Burke, R.: Feedback loop and bias amplification in recommender systems. In: Proceedings of the 29th ACM International Conference on Information & Knowledge Management, pp. 2145\u20132148. CIKM 2020, Association for Computing Machinery, New York, NY, USA (2020). https:\/\/doi.org\/10.1145\/3340531.3412152. https:\/\/doi-org.libproxy.aalto.fi\/10.1145\/3340531.3412152","DOI":"10.1145\/3340531.3412152"},{"key":"7_CR19","doi-asserted-by":"crossref","unstructured":"Reimers, N., Gurevych, I.: Sentence-BERT: sentence embeddings using Siamese BERT-networks. In: Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics (2019). http:\/\/arxiv.org\/abs\/1908.10084","DOI":"10.18653\/v1\/D19-1410"},{"key":"7_CR20","unstructured":"Wang, L., Schwing, A., Lazebnik, S.: Diverse and accurate image description using a variational auto-encoder with an additive gaussian encoding space. In: Guyon, I., Luxburg, U.V., Bengio, S., Wallach, H., Fergus, R., Vishwanathan, S., Garnett, R. (eds.) Advances in Neural Information Processing Systems, vol. 30. Curran Associates, Inc. (2017). https:\/\/proceedings.neurips.cc\/paper\/2017\/file\/4b21cf96d4cf612f239a6c322b10c8fe-Paper.pdf"},{"key":"7_CR21","unstructured":"Wasilewski, J., Hurley, N.: Incorporating diversity in a learning to rank recommender system. In: the Twenty-ninth International Flairs Conference (2016)"},{"key":"7_CR22","doi-asserted-by":"publisher","unstructured":"Zhang, Y., Wang, Y., Zhang, L., Zhang, Z., Gai, K.: Improve diverse text generation by self labeling conditional variational auto encoder. In: ICASSP 2019\u20132019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 2767\u20132771 (2019). https:\/\/doi.org\/10.1109\/ICASSP.2019.8683090","DOI":"10.1109\/ICASSP.2019.8683090"},{"key":"7_CR23","doi-asserted-by":"publisher","unstructured":"Ziegler, C.N., McNee, S.M., Konstan, J.A., Lausen, G.: Improving recommendation lists through topic diversification. In: Proceedings of the 14th International Conference on World Wide Web, pp. 22\u201332. WWW 2005, Association for Computing Machinery, New York, NY, USA (2005). https:\/\/doi.org\/10.1145\/1060745.1060754","DOI":"10.1145\/1060745.1060754"}],"container-title":["Communications in Computer and Information Science","Advances in Bias and Fairness in Information Retrieval"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-37249-0_7","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,7,14]],"date-time":"2023-07-14T04:02:59Z","timestamp":1689307379000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-37249-0_7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031372483","9783031372490"],"references-count":23,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-37249-0_7","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"15 July 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"BIAS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Workshop on Algorithmic Bias in Search and Recommendation","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Dublin","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Ireland","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":"2 April 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2 April 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ibpria2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/biasinrecsys.github.io\/ecir2023\/","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":"Easy Chair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"36","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":"10","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":"4","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":"28% - 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":"1","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":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}