{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T09:30:01Z","timestamp":1743154201754,"version":"3.40.3"},"publisher-location":"Cham","reference-count":13,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030609351"},{"type":"electronic","value":"9783030609368"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/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":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-3-030-60936-8_28","type":"book-chapter","created":{"date-parts":[[2020,10,14]],"date-time":"2020-10-14T10:05:52Z","timestamp":1602669952000},"page":"361-368","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Learning Distance Estimators from\u00a0Pivoted Embeddings of Metric Objects"],"prefix":"10.1007","author":[{"given":"Fabio","family":"Carrara","sequence":"first","affiliation":[]},{"given":"Claudio","family":"Gennaro","sequence":"additional","affiliation":[]},{"given":"Fabrizio","family":"Falchi","sequence":"additional","affiliation":[]},{"given":"Giuseppe","family":"Amato","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,10,14]]},"reference":[{"key":"28_CR1","doi-asserted-by":"crossref","unstructured":"Amato, G., Falchi, F., Gennaro, C., Rabitti, F.: YFCC100M hybridnet fc6 deep features for content-based image retrieval. In: Proceedings of the 2016 ACM Workshop on Multimedia COMMONS, pp. 11\u201318 (2016)","DOI":"10.1145\/2983554.2983557"},{"key":"28_CR2","volume-title":"Theory and Applications of Distance Geometry","author":"LM Blumenthal","year":"1953","unstructured":"Blumenthal, L.M.: Theory and Applications of Distance Geometry. Clarendon Press, Oxford (1953)"},{"issue":"3","key":"28_CR3","doi-asserted-by":"publisher","first-page":"17:1","DOI":"10.1145\/3001583","volume":"35","author":"R Connor","year":"2016","unstructured":"Connor, R., Cardillo, F.A., Vadicamo, L., Rabitti, F.: Hilbert exclusion: improved metric search through finite isometric embeddings. ACM Trans. Inf. Syst. 35(3), 17:1\u201317:27 (2016). https:\/\/doi.org\/10.1145\/3001583","journal-title":"ACM Trans. Inf. Syst."},{"key":"28_CR4","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1007\/978-3-319-46759-7_4","volume-title":"Similarity Search and Applications","author":"R Connor","year":"2016","unstructured":"Connor, R., Vadicamo, L., Cardillo, F.A., Rabitti, F.: Supermetric search with the four-point property. In: Amsaleg, L., Houle, M.E., Schubert, E. (eds.) SISAP 2016. LNCS, vol. 9939, pp. 51\u201364. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46759-7_4"},{"key":"28_CR5","doi-asserted-by":"publisher","first-page":"108","DOI":"10.1016\/j.is.2018.01.002","volume":"80","author":"R Connor","year":"2019","unstructured":"Connor, R., Vadicamo, L., Cardillo, F.A., Rabitti, F.: Supermetric search. Inf. Syst. 80, 108\u2013123 (2019)","journal-title":"Inf. Syst."},{"key":"28_CR6","doi-asserted-by":"publisher","unstructured":"Connor, R., Vadicamo, L., Rabitti, F.: High-dimensional simplexes for supermetric search. In: Beecks, C., Borutta, F., Kr\u00f6ger, P., Seidl, T. (eds.) Similarity Search and Applications, Proceedings of SISAP 2017, pp. 96\u2013109. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-68474-1_7","DOI":"10.1007\/978-3-319-68474-1_7"},{"key":"28_CR7","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 770\u2013778 (2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"28_CR8","doi-asserted-by":"publisher","DOI":"10.1145\/3183713.3196909","volume-title":"The Case for Learned Index Structures","author":"T Kraska","year":"2018","unstructured":"Kraska, T., Beutel, A., Chi, E.H., Dean, J., Polyzotis, N.: The Case for Learned Index Structures. Association for Computing Machinery, New York (2018)"},{"issue":"1","key":"28_CR9","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1016\/0167-8655(94)90095-7","volume":"15","author":"ML Mic\u00f3","year":"1994","unstructured":"Mic\u00f3, M.L., Oncina, J., Vidal, E.: A new version of the nearest-neighbour approximating and eliminating search algorithm (AESA) with linear preprocessing time and memory requirements. Pattern Recogn. Lett. 15(1), 9\u201317 (1994). https:\/\/doi.org\/10.1016\/0167-8655(94)90095-7","journal-title":"Pattern Recogn. Lett."},{"issue":"4","key":"28_CR10","doi-asserted-by":"publisher","first-page":"811","DOI":"10.2307\/1968466","volume":"39","author":"IJ Schoenberg","year":"1938","unstructured":"Schoenberg, I.J.: Metric spaces and completely monotone functions. Ann. Math. 39(4), 811\u2013841 (1938)","journal-title":"Ann. Math."},{"issue":"2","key":"28_CR11","doi-asserted-by":"publisher","first-page":"64","DOI":"10.1145\/2812802","volume":"59","author":"B Thomee","year":"2016","unstructured":"Thomee, B., et al.: YFCC100M: the new data in multimedia research. Commun. ACM 59(2), 64\u201373 (2016)","journal-title":"Commun. ACM"},{"key":"28_CR12","doi-asserted-by":"crossref","unstructured":"Vadicamo, L., Gennaro, C., Falchi, F., Ch\u00e1vez, E., Connor, R., Amato, G.: Re-ranking via local embeddings: a use case with permutation-based indexing and the nSimplex projection. Inf. Syst. 101506 (2020)","DOI":"10.1016\/j.is.2020.101506"},{"key":"28_CR13","unstructured":"Zhou, B., Lapedriza, A., Xiao, J., Torralba, A., Oliva, A.: Learning deep features for scene recognition using places database. In: Advances in Neural Information Processing Systems, pp. 487\u2013495 (2014)"}],"container-title":["Lecture Notes in Computer Science","Similarity Search and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-60936-8_28","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,12]],"date-time":"2024-03-12T13:45:46Z","timestamp":1710251146000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-60936-8_28"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030609351","9783030609368"],"references-count":13,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-60936-8_28","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":"14 October 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"SISAP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Similarity Search and Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Copenhagen","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Denmark","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":"30 September 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2 October 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"sisap2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.sisap.org\/2020\/","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":"50","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":"19","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":"12","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":"38% - 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":"3.9","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":"3","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":"2 short papers accepted for the SISAP 2020 Doctoral Symposium are also included. The conference was 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)"}}]}}