{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T20:31:13Z","timestamp":1742934673839,"version":"3.40.3"},"publisher-location":"Cham","reference-count":16,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031469930"},{"type":"electronic","value":"9783031469947"}],"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\/978-3-031-46994-7_18","type":"book-chapter","created":{"date-parts":[[2023,10,26]],"date-time":"2023-10-26T07:02:16Z","timestamp":1698303736000},"page":"215-222","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Vec2Doc: Transforming Dense Vectors into\u00a0Sparse Representations for\u00a0Efficient Information Retrieval"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5014-5089","authenticated-orcid":false,"given":"Fabio","family":"Carrara","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3715-149X","authenticated-orcid":false,"given":"Claudio","family":"Gennaro","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7182-7038","authenticated-orcid":false,"given":"Lucia","family":"Vadicamo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0171-4315","authenticated-orcid":false,"given":"Giuseppe","family":"Amato","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,10,27]]},"reference":[{"key":"18_CR1","doi-asserted-by":"crossref","unstructured":"Amato, G., Bolettieri, P., Carrara, F., Falchi, F., Gennaro, C.: Large-scale image retrieval with elasticsearch. In: The 41st International ACM SIGIR Conference on Research Development in Information Retrieval, pp. 925\u2013928 (2018)","DOI":"10.1145\/3209978.3210089"},{"issue":"6","key":"18_CR2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ipm.2019.102100","volume":"57","author":"G Amato","year":"2020","unstructured":"Amato, G., Carrara, F., Falchi, F., Gennaro, C., Vadicamo, L.: Large-scale instance-level image retrieval. Inf. Process. Manage. 57(6), 102100 (2020)","journal-title":"Inf. Process. Manage."},{"key":"18_CR3","doi-asserted-by":"crossref","unstructured":"Carrara, F., Vadicamo, L., Gennaro, C., Amato, G.: Approximate nearest neighbor search on standard search engines. In: Similarity Search and Applications: 15th International Conference, SISAP 2022, Bologna, Italy, October 5\u20137, 2022, Proceedings, pp. 214\u2013221. Springer (2022)","DOI":"10.1007\/978-3-031-17849-8_17"},{"issue":"9","key":"18_CR4","doi-asserted-by":"publisher","first-page":"1647","DOI":"10.1109\/TPAMI.2007.70815","volume":"30","author":"E Ch\u00e1vez","year":"2008","unstructured":"Ch\u00e1vez, E., Figueroa, K., Navarro, G.: Effective proximity retrieval by ordering permutations. IEEE Trans. Pattern Anal. Mach. Intell. 30(9), 1647\u20131658 (2008)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"18_CR5","unstructured":"Dua, D., Graff, C.: UCI machine learning repository (2017). http:\/\/archive.ics.uci.edu\/ml"},{"key":"18_CR6","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1007\/978-3-642-15464-5_8","volume-title":"Research and Advanced Technology for Digital Libraries","author":"C Gennaro","year":"2010","unstructured":"Gennaro, C., Amato, G., Bolettieri, P., Savino, P.: An Approach to Content-Based Image Retrieval Based on the Lucene Search Engine Library. In: Lalmas, M., Jose, J., Rauber, A., Sebastiani, F., Frommholz, I. (eds.) Research and Advanced Technology for Digital Libraries, pp. 55\u201366. Springer, Berlin, Heidelberg (2010). https:\/\/doi.org\/10.1007\/978-3-642-15464-5_8"},{"key":"18_CR7","doi-asserted-by":"crossref","unstructured":"Higuchi, N., Imamura, Y., Mic, V., Shinohara, T., Hirata, K., Kuboyama, T.: Nearest-neighbor search from large datasets using narrow sketches. In: ICPRAM, pp. 401\u2013410 (2022)","DOI":"10.5220\/0010817600003122"},{"issue":"1","key":"18_CR8","first-page":"1","volume":"37","author":"V Mic","year":"2018","unstructured":"Mic, V., Novak, D., Zezula, P.: Binary sketches for secondary filtering. ACM Trans. Inform. Syst. (TOIS) 37(1), 1\u201328 (2018)","journal-title":"ACM Trans. Inform. Syst. (TOIS)"},{"key":"18_CR9","doi-asserted-by":"crossref","unstructured":"Novak, D., Zezula, P.: Ppp-codes for large-scale similarity searching. Transactions on Large-Scale Data-and Knowledge-Centered Systems XXIV: Special Issue on Database-and Expert-Systems Applications, pp. 61\u201387 (2016)","DOI":"10.1007\/978-3-662-49214-7_2"},{"key":"18_CR10","doi-asserted-by":"crossref","unstructured":"Pennington, J., Socher, R., Manning, C.D.: GloVe: global vectors for word representation. In: Empirical Methods in Natural Language Processing (EMNLP), pp. 1532\u20131543 (2014)","DOI":"10.3115\/v1\/D14-1162"},{"key":"18_CR11","doi-asserted-by":"crossref","unstructured":"Povey, D., et al.: Semi-orthogonal low-rank matrix factorization for deep neural networks. In: Interspeech, pp. 3743\u20133747 (2018)","DOI":"10.21437\/Interspeech.2018-1417"},{"key":"18_CR12","volume-title":"Introduction to Modern Information Retrieval","author":"G Salton","year":"1986","unstructured":"Salton, G., McGill, M.J.: Introduction to Modern Information Retrieval. McGraw-Hill Inc, New York, NY, USA (1986)"},{"key":"18_CR13","unstructured":"Shang, W., Sohn, K., Almeida, D., Lee, H.: Understanding and improving convolutional neural networks via concatenated rectified linear units. In: Proceedings of the 33rd International Conference on Machine Learning. ICML 2016, vol. 48, pp. 2217\u20132225. JMLR.org (2016)"},{"key":"18_CR14","unstructured":"Simhadri, H.V., et al.: Results of the neurips\u201921 challenge on billion-scale approximate nearest neighbor search. In: NeurIPS 2021 Competitions and Demonstrations Track, pp. 177\u2013189. PMLR (2022)"},{"key":"18_CR15","doi-asserted-by":"publisher","DOI":"10.1016\/j.is.2021.101808","volume":"101","author":"L Vadicamo","year":"2021","unstructured":"Vadicamo, L., Connor, R., Ch\u00e1vez, E.: Query filtering using two-dimensional local embeddings. Inf. Syst. 101, 101808 (2021)","journal-title":"Inf. Syst."},{"key":"18_CR16","doi-asserted-by":"publisher","DOI":"10.1016\/j.is.2020.101506","volume":"95","author":"L Vadicamo","year":"2021","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. 95, 101506 (2021)","journal-title":"Inf. Syst."}],"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\/978-3-031-46994-7_18","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,10,26]],"date-time":"2023-10-26T07:03:59Z","timestamp":1698303839000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-46994-7_18"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031469930","9783031469947"],"references-count":16,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-46994-7_18","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"27 October 2023","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":"Coruna","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Spain","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":"9 October 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 October 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"sisap2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.sisap.org\/2023\/","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":"33","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":"16","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":"48% - 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":"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)"}},{"value":"Familiarity, LaTeX and LNCS friendly, steering committee has subscription","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)"}}]}}