{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T16:04:07Z","timestamp":1774541047278,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":34,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,5,13]],"date-time":"2024-05-13T00:00:00Z","timestamp":1715558400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,5,13]]},"DOI":"10.1145\/3589334.3645689","type":"proceedings-article","created":{"date-parts":[[2024,5,8]],"date-time":"2024-05-08T07:08:13Z","timestamp":1715152093000},"page":"3900-3909","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["Predictive Relevance Uncertainty for Recommendation Systems"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7827-1551","authenticated-orcid":false,"given":"Charul","family":"Paliwal","sequence":"first","affiliation":[{"name":"Amazon, Bengaluru, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6328-5002","authenticated-orcid":false,"given":"Anirban","family":"Majumder","sequence":"additional","affiliation":[{"name":"Amazon, Bengaluru, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-8888-6831","authenticated-orcid":false,"given":"Sivaramakrishnan","family":"Kaveri","sequence":"additional","affiliation":[{"name":"Amazon, Bengaluru, India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2024,5,13]]},"reference":[{"key":"e_1_3_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.5555\/1390681.1442792"},{"key":"e_1_3_2_2_2_1","first-page":"1613","volume-title":"International conference on machine learning","author":"Blundell C.","year":"2015","unstructured":"C. Blundell, J. Cornebise, K. Kavukcuoglu, and D. Wierstra. Weight uncertainty in neural network. In International conference on machine learning, pages 1613--1622. PMLR, 2015."},{"key":"e_1_3_2_2_3_1","volume-title":"Dexdeepfm: Ensemble diversity enhanced extreme deep factorization machine model. ACM Trans. Knowl. Discov. Data, 16(5), mar","author":"Chen L.","year":"2022","unstructured":"L. Chen and H. Shi. Dexdeepfm: Ensemble diversity enhanced extreme deep factorization machine model. ACM Trans. Knowl. Discov. Data, 16(5), mar 2022."},{"key":"e_1_3_2_2_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/2988450.2988454"},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5768"},{"key":"e_1_3_2_2_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/3584021"},{"key":"e_1_3_2_2_7_1","first-page":"1566","volume-title":"Proceedings of the 16th International Conference on Information Fusion","author":"Dragos V.","year":"2013","unstructured":"V. Dragos. An ontological analysis of uncertainty in soft data. In Proceedings of the 16th International Conference on Information Fusion, pages 1566--1573, 2013."},{"key":"e_1_3_2_2_8_1","volume-title":"Uncertainty in deep learning","author":"Gal Y.","year":"2016","unstructured":"Y. Gal et al. Uncertainty in deep learning. 2016."},{"key":"e_1_3_2_2_9_1","first-page":"1050","volume-title":"international conference on machine learning","author":"Gal Y.","year":"2016","unstructured":"Y. Gal and Z. Ghahramani. Dropout as a bayesian approximation: Representing model uncertainty in deep learning. In international conference on machine learning, pages 1050--1059. PMLR, 2016."},{"key":"e_1_3_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2017\/239"},{"key":"e_1_3_2_2_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-021-05946-3"},{"key":"e_1_3_2_2_13_1","doi-asserted-by":"publisher","DOI":"10.5555\/3295222.3295309"},{"key":"e_1_3_2_2_14_1","doi-asserted-by":"publisher","DOI":"10.5555\/3295222.3295309"},{"key":"e_1_3_2_2_15_1","doi-asserted-by":"publisher","DOI":"10.2196\/36427"},{"key":"e_1_3_2_2_16_1","doi-asserted-by":"publisher","DOI":"10.5555\/3295222.3295387"},{"key":"e_1_3_2_2_17_1","volume-title":"Simple and scalable predictive uncertainty estimation using deep ensembles. Advances in neural information processing systems, 30","author":"Lakshminarayanan B.","year":"2017","unstructured":"B. Lakshminarayanan, A. Pritzel, and C. Blundell. Simple and scalable predictive uncertainty estimation using deep ensembles. Advances in neural information processing systems, 30, 2017."},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3220023"},{"key":"e_1_3_2_2_19_1","first-page":"42","article-title":"A simple approach to improve single-model deep uncertainty via distance-awareness","volume":"24","author":"Liu J. Z.","year":"2023","unstructured":"J. Z. Liu, S. Padhy, J. Ren, Z. Lin, Y. Wen, G. Jerfel, Z. Nado, J. Snoek, D. Tran, and B. Lakshminarayanan. A simple approach to improve single-model deep uncertainty via distance-awareness. J. Mach. Learn. Res., 24:42--1, 2023.","journal-title":"J. Mach. Learn. Res."},{"key":"e_1_3_2_2_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.02336"},{"key":"e_1_3_2_2_21_1","unstructured":"B. Qin L. Wang B. Hui B. Li X. Wei B. Li F. Huang L. Si M. Yang and Y. Li. Sun: Exploring intrinsic uncertainties in text-to-sql parsers. In N. Calzolari C.-R. Huang H. Kim J. Pustejovsky L. Wanner K.-S. Choi P.-M. Ryu H.-H. Chen L. Donatelli H. Ji S. Kurohashi P. Paggio N. Xue S. Kim Y. Hahm Z. He T. K. Lee E. Santus F. Bond and S.-H. Na editors Proceedings of the 29th International Conference on Computational Linguistics COLING 2022 Gyeongju Republic of Korea October 12--17 2022 pages 5298--5308. International Committee on Computational Linguistics 2022."},{"key":"e_1_3_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2010.127"},{"key":"e_1_3_2_2_23_1","doi-asserted-by":"publisher","DOI":"10.5555\/3327144.3327239"},{"key":"e_1_3_2_2_24_1","unstructured":"B. Settles. Active learning literature survey. Computer Sciences Technical Report 1648 University of Wisconsin--Madison 2009."},{"key":"e_1_3_2_2_25_1","volume-title":"Apr.","author":"Valdenegro-Toro M.","year":"2022","unstructured":"M. Valdenegro-Toro and D. Saromo. A Deeper Look into Aleatoric and Epistemic Uncertainty Disentanglement. arXiv e-prints, page arXiv:2204.09308, Apr. 2022."},{"key":"e_1_3_2_2_26_1","volume-title":"On feature collapse and deep kernel learning for single forward pass uncertainty. arXiv preprint arXiv:2102.11409","author":"van Amersfoort J.","year":"2021","unstructured":"J. van Amersfoort, L. Smith, A. Jesson, O. Key, and Y. Gal. On feature collapse and deep kernel learning for single forward pass uncertainty. arXiv preprint arXiv:2102.11409, 2021."},{"key":"e_1_3_2_2_27_1","first-page":"9690","volume-title":"International conference on machine learning","author":"Van Amersfoort J.","year":"2020","unstructured":"J. Van Amersfoort, L. Smith, Y.W. Teh, and Y. Gal. Uncertainty estimation using a single deep deterministic neural network. In International conference on machine learning, pages 9690--9700. PMLR, 2020."},{"key":"e_1_3_2_2_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/3124749.3124754"},{"key":"e_1_3_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3450078"},{"key":"e_1_3_2_2_30_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.emnlp-main.216"},{"key":"e_1_3_2_2_31_1","doi-asserted-by":"publisher","DOI":"10.1145\/3477495.3531902"},{"key":"e_1_3_2_2_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219823"},{"key":"e_1_3_2_2_33_1","doi-asserted-by":"publisher","DOI":"10.1145\/3477495.3531723"},{"key":"e_1_3_2_2_34_1","doi-asserted-by":"publisher","DOI":"10.1145\/3459637.3482486"}],"event":{"name":"WWW '24: The ACM Web Conference 2024","location":"Singapore Singapore","acronym":"WWW '24","sponsor":["SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web"]},"container-title":["Proceedings of the ACM Web Conference 2024"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3589334.3645689","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3589334.3645689","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T00:27:44Z","timestamp":1755822464000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3589334.3645689"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,5,13]]},"references-count":34,"alternative-id":["10.1145\/3589334.3645689","10.1145\/3589334"],"URL":"https:\/\/doi.org\/10.1145\/3589334.3645689","relation":{},"subject":[],"published":{"date-parts":[[2024,5,13]]},"assertion":[{"value":"2024-05-13","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}