{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T14:30:16Z","timestamp":1742913016709,"version":"3.40.3"},"publisher-location":"Cham","reference-count":17,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030320461"},{"type":"electronic","value":"9783030320478"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-3-030-32047-8_5","type":"book-chapter","created":{"date-parts":[[2019,9,24]],"date-time":"2019-09-24T05:07:22Z","timestamp":1569301642000},"page":"49-56","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Fast and Exact Nearest Neighbor Search in Hamming Space on Full-Text Search Engines"],"prefix":"10.1007","author":[{"given":"Cun","family":"Mu","sequence":"first","affiliation":[]},{"given":"Jun","family":"Zhao","sequence":"additional","affiliation":[]},{"given":"Guang","family":"Yang","sequence":"additional","affiliation":[]},{"given":"Binwei","family":"Yang","sequence":"additional","affiliation":[]},{"given":"Zheng","family":"Yan","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,9,23]]},"reference":[{"key":"5_CR1","doi-asserted-by":"crossref","unstructured":"Amato, G., Bolettieri, P., Carrara, F., Falchi, F., Gennaro, C.: Large-scale image retrieval with elasticsearch. In: SIGIR (2018)","DOI":"10.1145\/3209978.3210089"},{"key":"5_CR2","unstructured":"Bernhardsson, E.: Annoy: Approximate Nearest Neighbors in C++\/Python (2018). Python package version 1.13.0. https:\/\/pypi.org\/project\/annoy\/"},{"key":"5_CR3","unstructured":"Beeler, M., Gosper, R.W., Schroeppel, R.: Hakmem. MIT Artificial Intelligence Laboratory (1972)"},{"key":"5_CR4","doi-asserted-by":"crossref","unstructured":"Gong, Y., Lazebnik, S.: Iterative quantization: a procrustean approach to learning binary codes. In: CVPR (2011)","DOI":"10.1109\/CVPR.2011.5995432"},{"key":"5_CR5","unstructured":"Johnson, J., Douze, M., J\u00e9gou, H.: Billion-scale similarity search with GPUs. arXiv preprint arXiv:1702.08734 (2017)"},{"key":"5_CR6","doi-asserted-by":"crossref","unstructured":"Li, G., Deng, D., Wang, J., Feng, J.: Pass-join: a partition-based method for similarity joins. In: VLDB (2012)","DOI":"10.14778\/2078331.2078340"},{"key":"5_CR7","doi-asserted-by":"crossref","unstructured":"Lux, M., Marques, O.: Visual Information Retrieval Using Java and LIRE, vol. 25. Morgan & Claypool Publishers (2013)","DOI":"10.1007\/978-3-031-02282-1_3"},{"key":"5_CR8","unstructured":"Mu, C., Yang, B., Yan, Z.: An empirical comparison of FAISS and FENSHSES for nearest neighbor search in hamming space. In: SIGIR eCommerce Workshop (2019)"},{"key":"5_CR9","unstructured":"Mu, C., Zhao, J., Yang, G., Zhang, J., Yan, Z.: Towards practical visual search engine within elasticsearch. In: SIGIR eCommerce Workshop (2018)"},{"issue":"11","key":"5_CR10","doi-asserted-by":"publisher","first-page":"2227","DOI":"10.1109\/TPAMI.2014.2321376","volume":"36","author":"M Muja","year":"2014","unstructured":"Muja, M., Lowe, D.G.: Scalable nearest neighbor algorithms for high dimensional data. IEEE Trans. Pattern Anal. Mach. Intell. 36(11), 2227\u20132240 (2014)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"5_CR11","doi-asserted-by":"crossref","unstructured":"Norouzi, M., Punjani, A., Fleet, D.J.: Fast search in hamming space with multi-index hashing. In: CVPR (2012)","DOI":"10.1109\/CVPR.2012.6248043"},{"key":"5_CR12","doi-asserted-by":"crossref","unstructured":"Qin, J., Wang, Y., Xiao, C., Wang, W., Lin, X., Ishikawa, Y.: GPH: similarity search in hamming space. In: ICDE (2018)","DOI":"10.1109\/ICDE.2018.00013"},{"key":"5_CR13","unstructured":"Ruzicka, M., Novotny, V., Sojka, P., Pomikalek, J., Rehurek, R.: Flexible similarity search of semantic vectors using fulltext search engines (2018). http:\/\/ceur-ws.org\/Vol-1923\/article-01.pdf"},{"key":"5_CR14","doi-asserted-by":"crossref","unstructured":"Rygl, J., Pomikalek, J., Rehurek, R., Ruzicka, M., Novotny, V., Sojka, P.: Semantic vector encoding and similarity search using fulltext search engines. In: RepL4NLP Workshop (2017)","DOI":"10.18653\/v1\/W17-2611"},{"key":"5_CR15","doi-asserted-by":"crossref","unstructured":"Szegedy, C., Ioffe, S., Vanhoucke, V., Alemi, A.: Inception-v4, Inception-Resnet and the impact of residual connections on learning. In: AAAI (2017)","DOI":"10.1609\/aaai.v31i1.11231"},{"key":"5_CR16","doi-asserted-by":"crossref","unstructured":"Wan, J., Tang, S., Zhang, Y., Huang, L., Li, J.: Data driven multi-index hashing. In: ICIP (2013)","DOI":"10.1109\/ICIP.2013.6738550"},{"key":"5_CR17","doi-asserted-by":"crossref","unstructured":"Yang, F., et al.: Visual search at ebay. In: KDD (2017)","DOI":"10.1145\/3097983.3098162"}],"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\/978-3-030-32047-8_5","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,13]],"date-time":"2024-03-13T10:44:39Z","timestamp":1710326679000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-32047-8_5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030320461","9783030320478"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-32047-8_5","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"23 September 2019","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":"Newark, NJ","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"USA","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2 October 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 October 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"sisap2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.sisap.org\/2019\/","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":"42","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":"12","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":"18","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":"29% - 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":"2.88","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":"1-92","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)"}}]}}