{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T06:36:17Z","timestamp":1772778977231,"version":"3.50.1"},"reference-count":52,"publisher":"Association for Computing Machinery (ACM)","issue":"10","content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["Proc. VLDB Endow."],"published-print":{"date-parts":[[2023,6]]},"abstract":"<jats:p>\n            Similarity search in high-dimensional metric spaces is routinely used in many applications including content-based image retrieval, bioinformatics, data mining, and recommender systems. Search can be accelerated by the use of an index. However, constructing a high-dimensional index can be quite expensive and may not pay off if the number of queries against the data is not large. In these circumstances, it is beneficial to construct an index\n            <jats:italic>adaptively<\/jats:italic>\n            , while responding to a query workload. Existing work on multidimensional adaptive indexing partitions space into orthotopes (i.e., hyperrectangular units). This approach, however, is highly ineffective in high-dimensional spaces. In this paper, we propose AV-tree: an alternative method for adaptive high-dimensional indexing that exploits previously computed distances, using query centers as vantage points. Our experimental study shows that AV-tree yields cumulative cost for the first several hundred or even thousand queries much lower than that of pre-built indices. After thousands of queries, the per-query performance of the AV-tree converges or even surpasses that of the state-of-the-art MVP-tree. Arguably, our approach is commendable in environments where the expected number of queries is not large while there is a need to start answering queries as soon as possible, such as applications where data are updated frequently and past data soon become obsolete.\n          <\/jats:p>","DOI":"10.14778\/3603581.3603592","type":"journal-article","created":{"date-parts":[[2023,8,8]],"date-time":"2023-08-08T19:06:48Z","timestamp":1691521608000},"page":"2525-2537","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":15,"title":["Adaptive Indexing in High-Dimensional Metric Spaces"],"prefix":"10.14778","volume":"16","author":[{"given":"Konstantinos","family":"Lampropoulos","sequence":"first","affiliation":[{"name":"University of Ioannina, Greece"}]},{"given":"Fatemeh","family":"Zardbani","sequence":"additional","affiliation":[{"name":"Aarhus University, Denmark"}]},{"given":"Nikos","family":"Mamoulis","sequence":"additional","affiliation":[{"name":"University of Ioannina, Greece"}]},{"given":"Panagiotis","family":"Karras","sequence":"additional","affiliation":[{"name":"Aarhus University, Denmark"}]}],"member":"320","published-online":{"date-parts":[[2023,8,8]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"crossref","first-page":"492","DOI":"10.14778\/2904121.2904125","article-title":"k-Nearest Neighbors on Road Networks: A Journey in Experimentation and In-Memory Implementation","volume":"9","author":"Abeywickrama Tenindra","year":"2016","unstructured":"Tenindra Abeywickrama , Muhammad Aamir Cheema , and David Taniar . 2016 . k-Nearest Neighbors on Road Networks: A Journey in Experimentation and In-Memory Implementation . Proc. VLDB Endow. 9 , 6 (2016), 492 -- 503 . Tenindra Abeywickrama, Muhammad Aamir Cheema, and David Taniar. 2016. k-Nearest Neighbors on Road Networks: A Journey in Experimentation and In-Memory Implementation. Proc. VLDB Endow. 9, 6 (2016), 492--503.","journal-title":"Proc. VLDB Endow."},{"key":"e_1_2_1_2_1","doi-asserted-by":"crossref","unstructured":"Takuya Akiba Yoichi Iwata and Yuichi Yoshida. 2013. Fast exact shortest-path distance queries on large networks by pruned landmark labeling. In SIGMOD. 349--360.  Takuya Akiba Yoichi Iwata and Yuichi Yoshida. 2013. Fast exact shortest-path distance queries on large networks by pruned landmark labeling. In SIGMOD. 349--360.","DOI":"10.1145\/2463676.2465315"},{"key":"e_1_2_1_3_1","volume-title":"NeurIPS","author":"Alvarez-Melis David","year":"2020","unstructured":"David Alvarez-Melis and Nicolo Fusi . 2020. Geometric Dataset Distances via Optimal Transport . In NeurIPS 2020 . David Alvarez-Melis and Nicolo Fusi. 2020. Geometric Dataset Distances via Optimal Transport. In NeurIPS 2020."},{"key":"e_1_2_1_4_1","doi-asserted-by":"crossref","first-page":"509","DOI":"10.1145\/361002.361007","article-title":"Multidimensional Binary Search Trees Used for Associative","volume":"18","author":"Bentley Jon Louis","year":"1975","unstructured":"Jon Louis Bentley . 1975 . Multidimensional Binary Search Trees Used for Associative Searching. Commun. ACM 18 , 9 (1975), 509 -- 517 . Jon Louis Bentley. 1975. Multidimensional Binary Search Trees Used for Associative Searching. Commun. ACM 18, 9 (1975), 509--517.","journal-title":"Searching. Commun. ACM"},{"key":"e_1_2_1_5_1","doi-asserted-by":"crossref","unstructured":"Kevin S. Beyer Jonathan Goldstein Raghu Ramakrishnan and Uri Shaft. 1999. When Is \"Nearest Neighbor\" Meaningful?. In ICDT. 217--235.  Kevin S. Beyer Jonathan Goldstein Raghu Ramakrishnan and Uri Shaft. 1999. When Is \"Nearest Neighbor\" Meaningful?. In ICDT. 217--235.","DOI":"10.1007\/3-540-49257-7_15"},{"key":"e_1_2_1_6_1","doi-asserted-by":"crossref","first-page":"361","DOI":"10.1145\/328939.328959","article-title":"Indexing Large Metric Spaces for Similarity Search Queries","volume":"24","author":"Bozkaya Tolga","year":"1999","unstructured":"Tolga Bozkaya and Meral Ozsoyoglu . 1999 . Indexing Large Metric Spaces for Similarity Search Queries . ACM Trans. Database Syst. 24 , 3 (1999), 361 -- 404 . Tolga Bozkaya and Meral Ozsoyoglu. 1999. Indexing Large Metric Spaces for Similarity Search Queries. ACM Trans. Database Syst. 24, 3 (1999), 361--404.","journal-title":"ACM Trans. Database Syst."},{"key":"e_1_2_1_7_1","volume-title":"Jensen","author":"Chen Lu","year":"2023","unstructured":"Lu Chen , Yunjun Gao , Xuan Song , Zheng Li , Yifan Zhu , Xiaoye Miao , and Christian S . Jensen . 2023 . Indexing Metric Spaces for Exact Similarity Search. ACM Comput. Surv . 55, 6 (2023), 128:1--128:39. Lu Chen, Yunjun Gao, Xuan Song, Zheng Li, Yifan Zhu, Xiaoye Miao, and Christian S. Jensen. 2023. Indexing Metric Spaces for Exact Similarity Search. ACM Comput. Surv. 55, 6 (2023), 128:1--128:39."},{"key":"e_1_2_1_8_1","doi-asserted-by":"crossref","first-page":"1058","DOI":"10.14778\/3115404.3115411","article-title":"Pivot-based Metric Indexing","volume":"10","author":"Chen Lu","year":"2017","unstructured":"Lu Chen , Yunjun Gao , Baihua Zheng , Christian S. Jensen , Hanyu Yang , and Keyu Yang . 2017 . Pivot-based Metric Indexing . Proc. VLDB Endow. 10 , 10 (2017), 1058 -- 1069 . Lu Chen, Yunjun Gao, Baihua Zheng, Christian S. Jensen, Hanyu Yang, and Keyu Yang. 2017. Pivot-based Metric Indexing. Proc. VLDB Endow. 10, 10 (2017), 1058--1069.","journal-title":"Proc. VLDB Endow."},{"key":"e_1_2_1_9_1","volume-title":"M-tree: An Efficient Access Method for Similarity Search in Metric Spaces. In VLDB. 426--435.","author":"Ciaccia Paolo","year":"1997","unstructured":"Paolo Ciaccia , Marco Patella , and Pavel Zezula . 1997 . M-tree: An Efficient Access Method for Similarity Search in Metric Spaces. In VLDB. 426--435. Paolo Ciaccia, Marco Patella, and Pavel Zezula. 1997. M-tree: An Efficient Access Method for Similarity Search in Metric Spaces. In VLDB. 426--435."},{"key":"e_1_2_1_10_1","first-page":"210","article-title":"A Tale of Four Metrics. In Similarity Search and Applications - 9th International Conference","volume":"9939","author":"Connor Richard","year":"2016","unstructured":"Richard Connor . 2016 . A Tale of Four Metrics. In Similarity Search and Applications - 9th International Conference , SISAP (Lecture Notes in Computer Science) , Vol. 9939. 210 -- 217 . Richard Connor. 2016. A Tale of Four Metrics. In Similarity Search and Applications - 9th International Conference, SISAP (Lecture Notes in Computer Science), Vol. 9939. 210--217.","journal-title":"SISAP (Lecture Notes in Computer Science)"},{"key":"e_1_2_1_11_1","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1109\/MSP.2012.2211477","article-title":"The MNIST Database of Handwritten Digit Images for Machine Learning Research [Best of the Web]","volume":"29","author":"Deng Li","year":"2012","unstructured":"Li Deng . 2012 . The MNIST Database of Handwritten Digit Images for Machine Learning Research [Best of the Web] . IEEE Signal Processing Magazine 29 , 6 (2012), 141 -- 142 . Li Deng. 2012. The MNIST Database of Handwritten Digit Images for Machine Learning Research [Best of the Web]. IEEE Signal Processing Magazine 29, 6 (2012), 141--142.","journal-title":"IEEE Signal Processing Magazine"},{"key":"e_1_2_1_12_1","volume-title":"Nature Communications 13","author":"Detlefsen Nicki Skafte","year":"2022","unstructured":"Nicki Skafte Detlefsen , S\u00f8ren Hauberg , and Wouter Boomsma . 2022 . Learning meaningful representations of protein sequences . Nature Communications 13 , 1914 (2022). Nicki Skafte Detlefsen, S\u00f8ren Hauberg, and Wouter Boomsma. 2022. Learning meaningful representations of protein sequences. Nature Communications 13, 1914 (2022)."},{"key":"e_1_2_1_13_1","doi-asserted-by":"crossref","first-page":"154","DOI":"10.1007\/PL00010672","article-title":"Dynamic vp-Tree Indexing for n-Nearest Neighbor Search Given Pair-Wise Distances","volume":"9","author":"Wai-Chee Fu Ada","year":"2000","unstructured":"Ada Wai-Chee Fu , Polly Mei-shuen Chan , Yin-Ling Cheung , and Yiu Sang Moon . 2000 . Dynamic vp-Tree Indexing for n-Nearest Neighbor Search Given Pair-Wise Distances . VLDB J. 9 , 2 (2000), 154 -- 173 . Ada Wai-Chee Fu, Polly Mei-shuen Chan, Yin-Ling Cheung, and Yiu Sang Moon. 2000. Dynamic vp-Tree Indexing for n-Nearest Neighbor Search Given Pair-Wise Distances. VLDB J. 9, 2 (2000), 154--173.","journal-title":"VLDB J."},{"key":"e_1_2_1_14_1","doi-asserted-by":"crossref","first-page":"461","DOI":"10.14778\/3303753.3303754","article-title":"Fast Approximate Nearest Neighbor Search With The Navigating Spreading-out Graph","volume":"12","author":"Fu Cong","year":"2019","unstructured":"Cong Fu , Chao Xiang , Changxu Wang , and Deng Cai . 2019 . Fast Approximate Nearest Neighbor Search With The Navigating Spreading-out Graph . Proc. VLDB Endow. 12 , 5 (2019), 461 -- 474 . Cong Fu, Chao Xiang, Changxu Wang, and Deng Cai. 2019. Fast Approximate Nearest Neighbor Search With The Navigating Spreading-out Graph. Proc. VLDB Endow. 12, 5 (2019), 461--474.","journal-title":"Proc. VLDB Endow."},{"key":"e_1_2_1_15_1","volume-title":"VLDB'99, Proceedings of 25th International Conference on Very Large Data Bases, September 7--10","author":"Gionis Aristides","year":"1999","unstructured":"Aristides Gionis , Piotr Indyk , and Rajeev Motwani . 1999. Similarity Search in High Dimensions via Hashing . In VLDB'99, Proceedings of 25th International Conference on Very Large Data Bases, September 7--10 , 1999 , Edinburgh, Scotland, UK . Morgan Kaufmann , 518--529. Aristides Gionis, Piotr Indyk, and Rajeev Motwani. 1999. Similarity Search in High Dimensions via Hashing. In VLDB'99, Proceedings of 25th International Conference on Very Large Data Bases, September 7--10, 1999, Edinburgh, Scotland, UK. Morgan Kaufmann, 518--529."},{"key":"e_1_2_1_16_1","volume-title":"Kuno","author":"Graefe Goetz","year":"2010","unstructured":"Goetz Graefe and Harumi A . Kuno . 2010 . Self-selecting, self-tuning, incrementally optimized indexes. In EDBT, Vol. 426 . ACM , 371--381. Goetz Graefe and Harumi A. Kuno. 2010. Self-selecting, self-tuning, incrementally optimized indexes. In EDBT, Vol. 426. ACM, 371--381."},{"key":"e_1_2_1_17_1","doi-asserted-by":"crossref","unstructured":"Antonin Guttman. 1984. R-Trees: A Dynamic Index Structure for Spatial Searching. In SIGMOD. 47--57.  Antonin Guttman. 1984. R-Trees: A Dynamic Index Structure for Spatial Searching. In SIGMOD. 47--57.","DOI":"10.1145\/971697.602266"},{"key":"e_1_2_1_18_1","doi-asserted-by":"crossref","first-page":"502","DOI":"10.14778\/2168651.2168652","article-title":"Stochastic Database Cracking: Towards Robust Adaptive Indexing in Main-Memory Column-Stores","volume":"5","author":"Halim Felix","year":"2012","unstructured":"Felix Halim , Stratos Idreos , Panagiotis Karras , and Roland H. C. Yap . 2012 . Stochastic Database Cracking: Towards Robust Adaptive Indexing in Main-Memory Column-Stores . Proc. VLDB Endow. 5 , 6 (2012), 502 -- 513 . Felix Halim, Stratos Idreos, Panagiotis Karras, and Roland H. C. Yap. 2012. Stochastic Database Cracking: Towards Robust Adaptive Indexing in Main-Memory Column-Stores. Proc. VLDB Endow. 5, 6 (2012), 502--513.","journal-title":"Proc. VLDB Endow."},{"key":"e_1_2_1_19_1","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1145\/366622.366644","article-title":"Algorithm 64","volume":"4","author":"Hoare C. A. R.","year":"1961","unstructured":"C. A. R. Hoare . 1961 . Algorithm 64 : Quicksort. Commun. ACM 4 , 7 (1961), 321 . C. A. R. Hoare. 1961. Algorithm 64: Quicksort. Commun. ACM 4, 7 (1961), 321.","journal-title":"Quicksort. Commun. ACM"},{"key":"e_1_2_1_20_1","doi-asserted-by":"crossref","first-page":"180","DOI":"10.1287\/moor.10.2.180","article-title":"A Best Possible Heuristic for the k-Center Problem","volume":"10","author":"Hochbaum Dorit","year":"1985","unstructured":"Dorit Hochbaum and David Shmoys . 1985 . A Best Possible Heuristic for the k-Center Problem . Mathematics of Operations Research - MOR 10 (1985), 180 -- 184 . Dorit Hochbaum and David Shmoys. 1985. A Best Possible Heuristic for the k-Center Problem. Mathematics of Operations Research - MOR 10 (1985), 180--184.","journal-title":"Mathematics of Operations Research - MOR"},{"key":"e_1_2_1_21_1","volume-title":"Progressive Mergesort: Merging Batches of Appends into Progressive Indexes. In EDBT. 481--486.","author":"Holanda Pedro","year":"2021","unstructured":"Pedro Holanda and Stefan Manegold . 2021 . Progressive Mergesort: Merging Batches of Appends into Progressive Indexes. In EDBT. 481--486. Pedro Holanda and Stefan Manegold. 2021. Progressive Mergesort: Merging Batches of Appends into Progressive Indexes. In EDBT. 481--486."},{"key":"e_1_2_1_22_1","doi-asserted-by":"crossref","first-page":"2366","DOI":"10.14778\/3358701.3358705","article-title":"Progressive Indexes: Indexing for Interactive Data Analysis","volume":"12","author":"Holanda Pedro","year":"2019","unstructured":"Pedro Holanda , Stefan Manegold , Hannes M\u00fchleisen , and Mark Raasveldt . 2019 . Progressive Indexes: Indexing for Interactive Data Analysis . Proc. VLDB Endow. 12 , 13 (2019), 2366 -- 2378 . Pedro Holanda, Stefan Manegold, Hannes M\u00fchleisen, and Mark Raasveldt. 2019. Progressive Indexes: Indexing for Interactive Data Analysis. Proc. VLDB Endow. 12, 13 (2019), 2366--2378.","journal-title":"Proc. VLDB Endow."},{"key":"e_1_2_1_23_1","doi-asserted-by":"crossref","unstructured":"Pedro Holanda Matheus Nerone Eduardo C. de Almeida and Stefan Manegold. 2018. Cracking KD-Tree: The First Multidimensional Adaptive Indexing (Position Paper). In DATA. 393--399.  Pedro Holanda Matheus Nerone Eduardo C. de Almeida and Stefan Manegold. 2018. Cracking KD-Tree: The First Multidimensional Adaptive Indexing (Position Paper). In DATA. 393--399.","DOI":"10.5220\/0006944203930399"},{"key":"e_1_2_1_24_1","unstructured":"Stratos Idreos Martin L. Kersten and Stefan Manegold. 2007. Database Cracking. In CIDR. 68--78.  Stratos Idreos Martin L. Kersten and Stefan Manegold. 2007. Database Cracking. In CIDR. 68--78."},{"key":"e_1_2_1_25_1","doi-asserted-by":"crossref","unstructured":"Stratos Idreos Martin L. Kersten and Stefan Manegold. 2007. Updating a Cracked Database. In SIGMOD. 413--424.  Stratos Idreos Martin L. Kersten and Stefan Manegold. 2007. Updating a Cracked Database. In SIGMOD. 413--424.","DOI":"10.1145\/1247480.1247527"},{"key":"e_1_2_1_26_1","doi-asserted-by":"crossref","unstructured":"Stratos Idreos Martin L. Kersten and Stefan Manegold. 2009. Self-organizing tuple reconstruction in column-stores. In SIGMOD. 297--308.  Stratos Idreos Martin L. Kersten and Stefan Manegold. 2009. Self-organizing tuple reconstruction in column-stores. In SIGMOD. 297--308.","DOI":"10.1145\/1559845.1559878"},{"key":"e_1_2_1_27_1","doi-asserted-by":"crossref","first-page":"586","DOI":"10.14778\/2002938.2002944","article-title":"Merging What's Cracked, Cracking What's Merged: Adaptive Indexing in Main-Memory Column-Stores","volume":"4","author":"Idreos Stratos","year":"2011","unstructured":"Stratos Idreos , Stefan Manegold , Harumi Kuno , and Goetz Graefe . 2011 . Merging What's Cracked, Cracking What's Merged: Adaptive Indexing in Main-Memory Column-Stores . Proc. VLDB Endow. 4 , 9 (2011), 586 -- 597 . Stratos Idreos, Stefan Manegold, Harumi Kuno, and Goetz Graefe. 2011. Merging What's Cracked, Cracking What's Merged: Adaptive Indexing in Main-Memory Column-Stores. Proc. VLDB Endow. 4, 9 (2011), 586--597.","journal-title":"Proc. VLDB Endow."},{"key":"e_1_2_1_28_1","doi-asserted-by":"crossref","unstructured":"Omid Jafari Parth Nagarkar and Jonathan Monta\u00c3\u015bo. 2020. Improving Locality Sensitive Hashing by Efficiently Finding Projected Nearest Neighbors.  Omid Jafari Parth Nagarkar and Jonathan Monta\u00c3\u015bo. 2020. Improving Locality Sensitive Hashing by Efficiently Finding Projected Nearest Neighbors.","DOI":"10.1007\/978-3-030-60936-8_25"},{"key":"e_1_2_1_29_1","doi-asserted-by":"crossref","first-page":"364","DOI":"10.1145\/1071610.1071612","article-title":"iDistance: An adaptive B+-tree based indexing method for nearest neighbor search","volume":"30","author":"Jagadish H. V.","year":"2005","unstructured":"H. V. Jagadish , Beng Chin Ooi , Kian-Lee Tan , Cui Yu , and Rui Zhang . 2005 . iDistance: An adaptive B+-tree based indexing method for nearest neighbor search . ACM Trans. Database Syst. 30 , 2 (2005), 364 -- 397 . H. V. Jagadish, Beng Chin Ooi, Kian-Lee Tan, Cui Yu, and Rui Zhang. 2005. iDistance: An adaptive B+-tree based indexing method for nearest neighbor search. ACM Trans. Database Syst. 30, 2 (2005), 364--397.","journal-title":"ACM Trans. Database Syst."},{"key":"e_1_2_1_30_1","unstructured":"Anders Hammersh\u00f8j Jensen Frederik Lauridsen Fatemeh Zardbani Stratos Idreos and Panagiotis Karras. 2021. Revisiting Multidimensional Adaptive Indexing [Experiment & Analysis]. In EDBT. 469--474.  Anders Hammersh\u00f8j Jensen Frederik Lauridsen Fatemeh Zardbani Stratos Idreos and Panagiotis Karras. 2021. Revisiting Multidimensional Adaptive Indexing [Experiment & Analysis]. In EDBT. 469--474."},{"key":"e_1_2_1_31_1","doi-asserted-by":"crossref","first-page":"883","DOI":"10.1137\/0217055","article-title":"Deferred Data Structuring","volume":"17","author":"Karp Richard M.","year":"1988","unstructured":"Richard M. Karp , Rajeev Motwani , and Prabhakar Raghavan . 1988 . Deferred Data Structuring . SIAM J. Comput. 17 , 5 (1988), 883 -- 902 . Richard M. Karp, Rajeev Motwani, and Prabhakar Raghavan. 1988. Deferred Data Structuring. SIAM J. Comput. 17, 5 (1988), 883--902.","journal-title":"SIAM J. Comput."},{"key":"e_1_2_1_32_1","article-title":"Hierarchical synopses with optimal error guarantees","volume":"33","author":"Karras Panagiotis","year":"2008","unstructured":"Panagiotis Karras and Nikos Mamoulis . 2008 . Hierarchical synopses with optimal error guarantees . ACM Trans. Database Syst. 33 , 3 (2008), 18:1--18:53. Panagiotis Karras and Nikos Mamoulis. 2008. Hierarchical synopses with optimal error guarantees. ACM Trans. Database Syst. 33, 3 (2008), 18:1--18:53.","journal-title":"ACM Trans. Database Syst."},{"key":"e_1_2_1_33_1","doi-asserted-by":"crossref","unstructured":"Panagiotis Karras Artyom Nikitin Muhammad Saad Rudrika Bhatt Denis Antyukhov and Stratos Idreos. 2016. Adaptive Indexing over Encrypted Numeric Data. In SIGMOD. 171--183.  Panagiotis Karras Artyom Nikitin Muhammad Saad Rudrika Bhatt Denis Antyukhov and Stratos Idreos. 2016. Adaptive Indexing over Encrypted Numeric Data. In SIGMOD. 171--183.","DOI":"10.1145\/2882903.2882932"},{"key":"e_1_2_1_34_1","volume-title":"Man Lung Yiu, and Nikos Mamoulis.","author":"Li Hui","year":"2017","unstructured":"Hui Li , Tsz Nam Chan , Man Lung Yiu, and Nikos Mamoulis. 2017 . FEXIPRO : Fast and Exact Inner Product Retrieval in Recommender Systems. In SIGMOD. 835--850. Hui Li, Tsz Nam Chan, Man Lung Yiu, and Nikos Mamoulis. 2017. FEXIPRO: Fast and Exact Inner Product Retrieval in Recommender Systems. In SIGMOD. 835--850."},{"key":"e_1_2_1_35_1","doi-asserted-by":"crossref","first-page":"488","DOI":"10.1111\/1556-4029.15196","article-title":"Research on the local regional similarity of automatic fingerprint identification system fingerprints based on close non-matches in a ten million people database - Taking the central region of whorl as an example","volume":"68","author":"Li Shuo","year":"2023","unstructured":"Shuo Li , Kang Li , Jun Yang , Yiwen Liu , Wenqiang Han , and Yaping Luo . 2023 . Research on the local regional similarity of automatic fingerprint identification system fingerprints based on close non-matches in a ten million people database - Taking the central region of whorl as an example . Journal of Forensic Sciences 68 , 2 (2023), 488 -- 499 . Shuo Li, Kang Li, Jun Yang, Yiwen Liu, Wenqiang Han, and Yaping Luo. 2023. Research on the local regional similarity of automatic fingerprint identification system fingerprints based on close non-matches in a ten million people database - Taking the central region of whorl as an example. Journal of Forensic Sciences 68, 2 (2023), 488--499.","journal-title":"Journal of Forensic Sciences"},{"key":"e_1_2_1_36_1","unstructured":"Wenye Li Jingwei Mao Yin Zhang and Shuguang Cui. 2018. Fast Similarity Search via Optimal Sparse Lifting. In NeurIPS. 176--184.  Wenye Li Jingwei Mao Yin Zhang and Shuguang Cui. 2018. Fast Similarity Search via Optimal Sparse Lifting. In NeurIPS. 176--184."},{"key":"e_1_2_1_37_1","doi-asserted-by":"crossref","first-page":"824","DOI":"10.1109\/TPAMI.2018.2889473","article-title":"Efficient and Robust Approximate Nearest Neighbor Search Using Hierarchical Navigable Small World Graphs","volume":"42","author":"Malkov Yury A.","year":"2020","unstructured":"Yury A. Malkov and Dmitry A. Yashunin . 2020 . Efficient and Robust Approximate Nearest Neighbor Search Using Hierarchical Navigable Small World Graphs . IEEE Trans. Pattern Anal. Mach. Intell. 42 , 4 (2020), 824 -- 836 . Yury A. Malkov and Dmitry A. Yashunin. 2020. Efficient and Robust Approximate Nearest Neighbor Search Using Hierarchical Navigable Small World Graphs. IEEE Trans. Pattern Anal. Mach. Intell. 42, 4 (2020), 824--836.","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"e_1_2_1_38_1","volume-title":"UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction. CoRR abs\/1802.03426","author":"McInnes Leland","year":"2018","unstructured":"Leland McInnes , John Healy , and James Melville . 2018 . UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction. CoRR abs\/1802.03426 (2018). arXiv:1802.03426 http:\/\/arxiv.org\/abs\/1802.03426 Leland McInnes, John Healy, and James Melville. 2018. UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction. CoRR abs\/1802.03426 (2018). arXiv:1802.03426 http:\/\/arxiv.org\/abs\/1802.03426"},{"key":"e_1_2_1_39_1","volume-title":"Workshop Track Proceedings.","author":"Mikolov Tom\u00e1s","year":"2013","unstructured":"Tom\u00e1s Mikolov , Kai Chen , Greg Corrado , and Jeffrey Dean . 2013 . Efficient Estimation of Word Representations in Vector Space. In ICLR , Workshop Track Proceedings. Tom\u00e1s Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean. 2013. Efficient Estimation of Word Representations in Vector Space. In ICLR, Workshop Track Proceedings."},{"key":"e_1_2_1_40_1","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1007\/s007780200060","article-title":"Searching in metric spaces by spatial approximation","volume":"11","author":"Navarro Gonzalo","year":"2002","unstructured":"Gonzalo Navarro . 2002 . Searching in metric spaces by spatial approximation . VLDB J. 11 , 1 (2002), 28 -- 46 . Gonzalo Navarro. 2002. Searching in metric spaces by spatial approximation. VLDB J. 11, 1 (2002), 28--46.","journal-title":"VLDB J."},{"key":"e_1_2_1_41_1","doi-asserted-by":"crossref","unstructured":"Matheus Agio Nerone Pedro Holanda Eduardo C. de Almeida and Stefan Manegold. 2021. Multidimensional Adaptive & Progressive Indexes. In ICDE. 624--635.  Matheus Agio Nerone Pedro Holanda Eduardo C. de Almeida and Stefan Manegold. 2021. Multidimensional Adaptive & Progressive Indexes. In ICDE. 624--635.","DOI":"10.1109\/ICDE51399.2021.00060"},{"key":"e_1_2_1_42_1","volume-title":"QUASII: QUery-Aware Spatial Incremental Index. In EDBT. 325--336.","author":"Pavlovic Mirjana","year":"2018","unstructured":"Mirjana Pavlovic , Darius Sidlauskas , Thomas Heinis , and Anastasia Ailamaki . 2018 . QUASII: QUery-Aware Spatial Incremental Index. In EDBT. 325--336. Mirjana Pavlovic, Darius Sidlauskas, Thomas Heinis, and Anastasia Ailamaki. 2018. QUASII: QUery-Aware Spatial Incremental Index. In EDBT. 325--336."},{"key":"e_1_2_1_43_1","first-page":"2825","article-title":"Scikit-learn: Machine Learning in Python","volume":"12","author":"Pedregosa F.","year":"2011","unstructured":"F. Pedregosa , G. Varoquaux , A. Gramfort , V. Michel , B. Thirion , O. Grisel , M. Blondel , P. Prettenhofer , R. Weiss , V. Dubourg , J. Vanderplas , A. Passos , D. Cournapeau , M. Brucher , M. Perrot , and E. Duchesnay . 2011 . Scikit-learn: Machine Learning in Python . Journal of Machine Learning Research 12 (2011), 2825 -- 2830 . F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, P. Prettenhofer, R. Weiss, V. Dubourg, J. Vanderplas, A. Passos, D. Cournapeau, M. Brucher, M. Perrot, and E. Duchesnay. 2011. Scikit-learn: Machine Learning in Python. Journal of Machine Learning Research 12 (2011), 2825--2830.","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_2_1_44_1","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1006\/jvci.1999.0413","article-title":"Image Retrieval: Current Techniques, Promising Directions, and Open Issues","volume":"10","author":"Rui Yong","year":"1999","unstructured":"Yong Rui , Thomas S. Huang , and Shih-Fu Chang . 1999 . Image Retrieval: Current Techniques, Promising Directions, and Open Issues . J. Vis. Commun. Image Represent. 10 , 1 (1999), 39 -- 62 . Yong Rui, Thomas S. Huang, and Shih-Fu Chang. 1999. Image Retrieval: Current Techniques, Promising Directions, and Open Issues. J. Vis. Commun. Image Represent. 10, 1 (1999), 39--62.","journal-title":"J. Vis. Commun. Image Represent."},{"key":"e_1_2_1_45_1","doi-asserted-by":"crossref","first-page":"97","DOI":"10.14778\/2732228.2732229","article-title":"The Uncracked Pieces in Database Cracking","volume":"7","author":"Schuhknecht Felix Martin","year":"2013","unstructured":"Felix Martin Schuhknecht , Alekh Jindal , and Jens Dittrich . 2013 . The Uncracked Pieces in Database Cracking . Proc. VLDB Endow. 7 , 2 (2013), 97 -- 108 . Felix Martin Schuhknecht, Alekh Jindal, and Jens Dittrich. 2013. The Uncracked Pieces in Database Cracking. Proc. VLDB Endow. 7, 2 (2013), 97--108.","journal-title":"Proc. VLDB Endow."},{"key":"e_1_2_1_46_1","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1007\/s00778-015-0397-y","article-title":"An Experimental Evaluation and Analysis of Database Cracking","volume":"25","author":"Schuhknecht Felix Martin","year":"2016","unstructured":"Felix Martin Schuhknecht , Alekh Jindal , and Jens Dittrich . 2016 . An Experimental Evaluation and Analysis of Database Cracking . The VLDB Journal 25 , 1 (2016), 27 -- 52 . Felix Martin Schuhknecht, Alekh Jindal, and Jens Dittrich. 2016. An Experimental Evaluation and Analysis of Database Cracking. The VLDB Journal 25, 1 (2016), 27--52.","journal-title":"The VLDB Journal"},{"key":"e_1_2_1_47_1","unstructured":"Tom\u00e1s Skopal Jaroslav Pokorn\u00fd and V\u00e1clav Sn\u00e1sel. 2004. PM-tree: Pivoting Metric Tree for Similarity Search in Multimedia Databases. In ADBIS.  Tom\u00e1s Skopal Jaroslav Pokorn\u00fd and V\u00e1clav Sn\u00e1sel. 2004. PM-tree: Pivoting Metric Tree for Similarity Search in Multimedia Databases. In ADBIS."},{"key":"e_1_2_1_48_1","doi-asserted-by":"crossref","unstructured":"Yao Tian Xi Zhao and Xiaofang Zhou. 2022. DB-LSH: Locality-Sensitive Hashing with Query-based Dynamic Bucketing. In ICDE. 2250--2262.  Yao Tian Xi Zhao and Xiaofang Zhou. 2022. DB-LSH: Locality-Sensitive Hashing with Query-based Dynamic Bucketing. In ICDE. 2250--2262.","DOI":"10.1109\/ICDE53745.2022.00214"},{"key":"e_1_2_1_49_1","unstructured":"Anton Tsitsulin Marina Munkhoeva Davide Mottin Panagiotis Karras Alexander M. Bronstein Ivan V. Oseledets and Emmanuel M\u00fcller. 2020. The Shape of Data: Intrinsic Distance for Data Distributions. In ICLR.  Anton Tsitsulin Marina Munkhoeva Davide Mottin Panagiotis Karras Alexander M. Bronstein Ivan V. Oseledets and Emmanuel M\u00fcller. 2020. The Shape of Data: Intrinsic Distance for Data Distributions. In ICLR."},{"key":"e_1_2_1_50_1","unstructured":"Peter N. Yianilos. 1993. Data Structures and Algorithms for Nearest Neighbor Search in General Metric Spaces. In SODA. 311--321.  Peter N. Yianilos. 1993. Data Structures and Algorithms for Nearest Neighbor Search in General Metric Spaces. In SODA. 311--321."},{"key":"e_1_2_1_51_1","unstructured":"Fatemeh Zardbani Peyman Afshani and Panagiotis Karras. 2020. Revisiting the Theory and Practice of Database Cracking. In EDBT. 415--418.  Fatemeh Zardbani Peyman Afshani and Panagiotis Karras. 2020. Revisiting the Theory and Practice of Database Cracking. In EDBT. 415--418."},{"key":"e_1_2_1_52_1","doi-asserted-by":"crossref","first-page":"2248","DOI":"10.14778\/3598581.3598596","article-title":"Adaptive Indexing of Objects with Spatial Extent","volume":"16","author":"Zardbani Fatemeh","year":"2023","unstructured":"Fatemeh Zardbani , Nikos Mamoulis , Stratos Idreos , and Panagiotis Karras . 2023 . Adaptive Indexing of Objects with Spatial Extent . Proc. VLDB Endow. 16 , 9 (2023), 2248 -- 2260 . Fatemeh Zardbani, Nikos Mamoulis, Stratos Idreos, and Panagiotis Karras. 2023. Adaptive Indexing of Objects with Spatial Extent. Proc. VLDB Endow. 16, 9 (2023), 2248--2260.","journal-title":"Proc. VLDB Endow."}],"container-title":["Proceedings of the VLDB Endowment"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.14778\/3603581.3603592","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,8,8]],"date-time":"2023-08-08T19:12:27Z","timestamp":1691521947000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.14778\/3603581.3603592"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,6]]},"references-count":52,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2023,6]]}},"alternative-id":["10.14778\/3603581.3603592"],"URL":"https:\/\/doi.org\/10.14778\/3603581.3603592","relation":{},"ISSN":["2150-8097"],"issn-type":[{"value":"2150-8097","type":"print"}],"subject":[],"published":{"date-parts":[[2023,6]]},"assertion":[{"value":"2023-08-08","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}