{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T07:30:02Z","timestamp":1743147002174,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":20,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819723898"},{"type":"electronic","value":"9789819723904"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"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":[[2024]]},"DOI":"10.1007\/978-981-97-2390-4_3","type":"book-chapter","created":{"date-parts":[[2024,4,27]],"date-time":"2024-04-27T18:02:02Z","timestamp":1714240922000},"page":"28-43","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["P-QALSH+: Exploiting Multiple Cores to\u00a0Parallelize Query-Aware Locality-Sensitive Hashing on\u00a0Big Data"],"prefix":"10.1007","author":[{"given":"Yikai","family":"Huang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zezhao","family":"Hu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianlin","family":"Feng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,4,28]]},"reference":[{"key":"3_CR1","doi-asserted-by":"crossref","unstructured":"Anastasiu, D.C., Rangwala, H., Tagarelli, A.: Are you my neighbor? Bringing order to neighbor computing problems. In: SIGKDD. KDD 2019 (2019)","DOI":"10.1145\/3292500.3332292"},{"key":"3_CR2","doi-asserted-by":"crossref","unstructured":"Datar, M., Immorlica, N., Indyk, P., Mirrokni, V.S.: Locality-sensitive hashing scheme based on p-stable distributions. In: SoCG, pp. 253\u2013262 (2004)","DOI":"10.1145\/997817.997857"},{"issue":"12","key":"3_CR3","first-page":"3198","volume":"14","author":"K Echihabi","year":"2021","unstructured":"Echihabi, K., Palpanas, T., Zoumpatianos, K.: New trends in high-d vector similarity search: AI-driven, progressive and distributed. VLDB 14(12), 3198\u20133201 (2021)","journal-title":"VLDB"},{"key":"3_CR4","doi-asserted-by":"crossref","unstructured":"Echihabi, K., Zoumpatianos, K., Palpanas, T.: High-dimensional similarity search for scalable data science. In: ICDE. ICDE 2021 (2021)","DOI":"10.1109\/ICDE51399.2021.00268"},{"key":"3_CR5","doi-asserted-by":"crossref","unstructured":"Gan, J., Feng, J., Fang, Q., Ng, W.: Locality-sensitive hashing scheme based on dynamic collision counting. In: SIGMOD, pp. 541\u2013552 (2012)","DOI":"10.1145\/2213836.2213898"},{"issue":"1","key":"3_CR6","first-page":"1","volume":"9","author":"Q Huang","year":"2015","unstructured":"Huang, Q., Feng, J., Zhang, Y., Fang, Q., Ng, W.: Query-aware locality-sensitive hashing for approximate nearest neighbor search. VLDB 9(1), 1\u201312 (2015)","journal-title":"VLDB"},{"key":"3_CR7","doi-asserted-by":"crossref","unstructured":"Huang, Y., Yao, Z., Feng, J.: P-QALSH: parallelizing query aware locality-sensitive hashing for big data. In: International Conference on Big Data (Big Data), Orlando, FL, USA, 15\u201318 December 2021, pp. 629\u2013634. IEEE (2021)","DOI":"10.1109\/BigData52589.2021.9671881"},{"key":"3_CR8","doi-asserted-by":"crossref","unstructured":"Indyk, P., Motwani, R.: Approximate nearest neighbors: towards removing the curse of dimensionality. In: STOC, pp. 604\u2013613 (1998)","DOI":"10.1145\/276698.276876"},{"key":"3_CR9","unstructured":"Jafari, O., Maurya, P., Nagarkar, P., Islam, K.M., Crushev, C.: A survey on locality sensitive hashing algorithms and their applications. arXiv:2102.08942 (2021)"},{"key":"3_CR10","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"323","DOI":"10.1007\/978-3-030-60936-8_25","volume-title":"Similarity Search and Applications","author":"O Jafari","year":"2020","unstructured":"Jafari, O., Nagarkar, P., Monta\u00f1o, J.: Improving locality sensitive hashing by efficiently finding projected nearest neighbors. In: Satoh, S., et al. (eds.) SISAP 2020. LNCS, vol. 12440, pp. 323\u2013337. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-60936-8_25"},{"key":"3_CR11","first-page":"1475","volume":"32","author":"W Li","year":"2016","unstructured":"Li, W., Zhang, Y., Sun, Y., Wang, W., Zhang, W., Lin, X.: Approximate nearest neighbor search on high dimensional data\u2013experiments, analyses, and improvement. TKDE 32, 1475\u20131488 (2016)","journal-title":"TKDE"},{"key":"3_CR12","doi-asserted-by":"crossref","unstructured":"Liu, W., Wang, H., Zhang, Y., Wang, W., Qin, L.: I-LSH: I\/O efficient C-approximate nearest neighbor search in high-dimensional space. In: ICDE, pp. 1670\u20131673 (2019)","DOI":"10.1109\/ICDE.2019.00169"},{"issue":"2","key":"3_CR13","doi-asserted-by":"publisher","first-page":"215","DOI":"10.1007\/s00778-020-00635-4","volume":"30","author":"W Liu","year":"2021","unstructured":"Liu, W., Wang, H., Zhang, Y., Wang, W., Qin, L., Lin, X.: EI-LSH: an early-termination driven I\/O efficient incremental c-approximate nearest neighbor search. VLDB J. 30(2), 215\u2013235 (2021)","journal-title":"VLDB J."},{"key":"3_CR14","doi-asserted-by":"crossref","unstructured":"Lu, K., Kudo, M.: R2LSH: a nearest neighbor search scheme based on two-dimensional projected spaces. In: ICDE, pp. 1045\u20131056 (2020)","DOI":"10.1109\/ICDE48307.2020.00095"},{"issue":"9","key":"3_CR15","first-page":"1443","volume":"13","author":"K Lu","year":"2020","unstructured":"Lu, K., Wang, H., Wang, W., Kudo, M.: VHP: approximate nearest neighbor search via virtual hypersphere partitioning. VLDB 13(9), 1443\u20131455 (2020)","journal-title":"VLDB"},{"issue":"1","key":"3_CR16","first-page":"1","volume":"8","author":"Y Sun","year":"2014","unstructured":"Sun, Y., Wang, W., Qin, J., Zhang, Y., Lin, X.: SRS: solving c-approximate nearest neighbor queries in high dimensional Euclidean space with a tiny index. VLDB 8(1), 1\u201312 (2014)","journal-title":"VLDB"},{"key":"3_CR17","doi-asserted-by":"crossref","unstructured":"Tao, Y., Yi, K., Sheng, C., Kalnis, P.: Efficient and accurate nearest neighbor and closest pair search in high-dimensional space. TODS 35(3), 20:1\u201320:46 (2010)","DOI":"10.1145\/1806907.1806912"},{"key":"3_CR18","unstructured":"Weber, R., Schek, H.J., Blott, S.: A quantitative analysis and performance study for similarity-search methods in high-dimensional spaces. In: VLDB, vol.\u00a098, pp. 194\u2013205 (1998)"},{"key":"3_CR19","doi-asserted-by":"crossref","unstructured":"Yang, C., Deng, D., Shang, S., Shao, L.: Efficient locality-sensitive hashing over high-dimensional data streams. In: ICDE, pp. 1986\u20131989 (2020)","DOI":"10.1109\/ICDE48307.2020.00220"},{"key":"3_CR20","doi-asserted-by":"crossref","unstructured":"Zhang, S., Huang, J., Xiao, R., Du, X., Gong, P., Lin, X.: Toward more efficient locality-sensitive hashing via constructing novel hash function cluster. Concurr. Comput. Pract. Exp. 33(20) (2021)","DOI":"10.1002\/cpe.6355"}],"container-title":["Lecture Notes in Computer Science","Web and Big Data"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-97-2390-4_3","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,4,27]],"date-time":"2024-04-27T18:11:31Z","timestamp":1714241491000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-97-2390-4_3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9789819723898","9789819723904"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-981-97-2390-4_3","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"28 April 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"APWeb-WAIM","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Asia-Pacific Web (APWeb) and Web-Age Information Management (WAIM) Joint International Conference on Web and Big Data","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Wuhan","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","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":"6 October 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 October 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"apwebwaim2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.apweb-waim2023.com\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}