{"id":"https://openalex.org/W2217456271","doi":"https://doi.org/10.14778/2732219.2732220","title":"Efficient and effective KNN sequence search with approximate n-grams","display_name":"Efficient and effective KNN sequence search with approximate n-grams","publication_year":2013,"publication_date":"2013-09-01","ids":{"openalex":"https://openalex.org/W2217456271","doi":"https://doi.org/10.14778/2732219.2732220","mag":"2217456271"},"language":"en","primary_location":{"id":"doi:10.14778/2732219.2732220","is_oa":false,"landing_page_url":"https://doi.org/10.14778/2732219.2732220","pdf_url":null,"source":{"id":"https://openalex.org/S4210226185","display_name":"Proceedings of the VLDB Endowment","issn_l":"2150-8097","issn":["2150-8097"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the VLDB Endowment","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100456913","display_name":"Xiaoli Wang","orcid":"https://orcid.org/0000-0002-8677-9080"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Xiaoli Wang","raw_affiliation_strings":["National University of Singapore"],"affiliations":[{"raw_affiliation_string":"National University of Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038493361","display_name":"Xiaofeng Ding","orcid":"https://orcid.org/0000-0001-5054-8515"},"institutions":[{"id":"https://openalex.org/I170239107","display_name":"University of South Australia","ror":"https://ror.org/01p93h210","country_code":"AU","type":"education","lineage":["https://openalex.org/I170239107"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Xiaofeng Ding","raw_affiliation_strings":["Huazhong University of Sci. & Tech. and University of South Australia"],"affiliations":[{"raw_affiliation_string":"Huazhong University of Sci. & Tech. and University of South Australia","institution_ids":["https://openalex.org/I170239107"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023925931","display_name":"Anthony K. H. Tung","orcid":"https://orcid.org/0000-0002-5125-855X"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Anthony K. H. Tung","raw_affiliation_strings":["National University of Singapore"],"affiliations":[{"raw_affiliation_string":"National University of Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100633297","display_name":"Zhenjie Zhang","orcid":"https://orcid.org/0009-0000-9080-7489"},"institutions":[{"id":"https://openalex.org/I4210108443","display_name":"Advanced Digital Sciences Center","ror":"https://ror.org/01xaqx887","country_code":"SG","type":"facility","lineage":["https://openalex.org/I4210108443"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Zhenjie Zhang","raw_affiliation_strings":["Advanced Digital Sciences Center"],"affiliations":[{"raw_affiliation_string":"Advanced Digital Sciences Center","institution_ids":["https://openalex.org/I4210108443"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100456913"],"corresponding_institution_ids":["https://openalex.org/I165932596"],"apc_list":null,"apc_paid":null,"fwci":5.9308,"has_fulltext":false,"cited_by_count":30,"citation_normalized_percentile":{"value":0.96066832,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"7","issue":"1","first_page":"1","last_page":"12"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11269","display_name":"Algorithms and Data Compression","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11269","display_name":"Algorithms and Data Compression","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9961000084877014,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8053447008132935},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.8046914339065552},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.7155075073242188},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.6750441193580627},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.5546509027481079},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5467159152030945},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5127618908882141},{"id":"https://openalex.org/keywords/basis","display_name":"Basis (linear algebra)","score":0.46237561106681824},{"id":"https://openalex.org/keywords/n-gram","display_name":"n-gram","score":0.44847628474235535},{"id":"https://openalex.org/keywords/nearest-neighbor-search","display_name":"Nearest neighbor search","score":0.43498462438583374},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.40454214811325073},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3145269751548767},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1209593415260315},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.0787147581577301},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.07644763588905334}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8053447008132935},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.8046914339065552},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.7155075073242188},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.6750441193580627},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.5546509027481079},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5467159152030945},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5127618908882141},{"id":"https://openalex.org/C12426560","wikidata":"https://www.wikidata.org/wiki/Q189569","display_name":"Basis (linear algebra)","level":2,"score":0.46237561106681824},{"id":"https://openalex.org/C117884012","wikidata":"https://www.wikidata.org/wiki/Q94489","display_name":"n-gram","level":3,"score":0.44847628474235535},{"id":"https://openalex.org/C116738811","wikidata":"https://www.wikidata.org/wiki/Q608751","display_name":"Nearest neighbor search","level":2,"score":0.43498462438583374},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.40454214811325073},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3145269751548767},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1209593415260315},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.0787147581577301},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.07644763588905334},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.14778/2732219.2732220","is_oa":false,"landing_page_url":"https://doi.org/10.14778/2732219.2732220","pdf_url":null,"source":{"id":"https://openalex.org/S4210226185","display_name":"Proceedings of the VLDB Endowment","issn_l":"2150-8097","issn":["2150-8097"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the VLDB Endowment","raw_type":"journal-article"},{"id":"pmh:oai:scholarbank.nus.edu.sg:10635/77845","is_oa":false,"landing_page_url":"http://scholarbank.nus.edu.sg/handle/10635/77845","pdf_url":null,"source":{"id":"https://openalex.org/S7407052290","display_name":"National University of Singapore","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Scopus","raw_type":"Article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.413.2543","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.413.2543","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.vldb.org/pvldb/vol7/p1-wang.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320312066","display_name":"Advanced Digital Sciences Center","ror":"https://ror.org/01xaqx887"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W1484435918","https://openalex.org/W1490635997","https://openalex.org/W1572771982","https://openalex.org/W1580725209","https://openalex.org/W1591155856","https://openalex.org/W1973001156","https://openalex.org/W1980038595","https://openalex.org/W1995074666","https://openalex.org/W2001496424","https://openalex.org/W2012010763","https://openalex.org/W2043481183","https://openalex.org/W2067789269","https://openalex.org/W2073329022","https://openalex.org/W2096598900","https://openalex.org/W2099370490","https://openalex.org/W2100548092","https://openalex.org/W2108378253","https://openalex.org/W2113875810","https://openalex.org/W2115214414","https://openalex.org/W2119057313","https://openalex.org/W2121269638","https://openalex.org/W2123020735","https://openalex.org/W2125708920","https://openalex.org/W2134206624","https://openalex.org/W2148148676","https://openalex.org/W2152618599","https://openalex.org/W2161936973","https://openalex.org/W2162592052","https://openalex.org/W2167847032","https://openalex.org/W2222512263","https://openalex.org/W6629116644","https://openalex.org/W6635148446","https://openalex.org/W6674576723","https://openalex.org/W6683401941"],"related_works":["https://openalex.org/W2373300491","https://openalex.org/W1212596013","https://openalex.org/W2378744544","https://openalex.org/W2906970013","https://openalex.org/W2594301978","https://openalex.org/W2379704676","https://openalex.org/W4206442282","https://openalex.org/W3126081632","https://openalex.org/W2384505857","https://openalex.org/W2355171581"],"abstract_inverted_index":{"In":[0],"this":[1,62,83],"paper,":[2],"we":[3,65],"address":[4],"the":[5,17,78,92,96,149,152],"problem":[6],"of":[7,56,151],"finding":[8],"k":[9],"-nearest":[10],"neighbors":[11],"(KNN)":[12],"in":[13,77],"sequence":[14,38,79],"databases":[15],"using":[16,24],"edit":[18],"distance.":[19],"Unlike":[20],"most":[21],"existing":[22,108],"works":[23],"short":[25],"and":[26,95,129,132],"exact":[27],"n":[28,50],"-gram":[29,51],"matchings":[30,52],"together":[31,85],"with":[32,86],"a":[33,54,67,71],"filter-and-refine":[34],"framework":[35,69,84],"for":[36,74],"KNN":[37,57,76],"search,":[39],"our":[40,101],"new":[41,63],"approach":[42],"allows":[43],"us":[44],"to":[45,118,136,147],"use":[46],"longer":[47],"but":[48],"approximate":[49],"as":[53],"basis":[55],"candidates":[58,117],"pruning.":[59],"Based":[60],"on":[61,114,122,143],"idea,":[64],"devise":[66],"pipeline":[68],"over":[70,107],"two-level":[72],"index":[73],"searching":[75],"database.":[80],"By":[81],"coupling":[82],"several":[87],"efficient":[88],"filtering":[89],"strategies,":[90],"i.e.":[91],"frequency":[93],"queue":[94],"well-known":[97],"Combined":[98],"Algorithm":[99],"(CA),":[100],"proposal":[102],"brings":[103],"various":[104],"enticing":[105],"advantages":[106],"works,":[109],"including":[110],"1)":[111],"huge":[112],"reduction":[113],"false":[115],"positive":[116],"avoid":[119],"large":[120],"overheads":[121],"candidate":[123],"verifications;":[124],"2)":[125],"progressive":[126],"result":[127],"update":[128],"early":[130],"termination;":[131],"3)":[133],"good":[134],"extensibility":[135],"parallel":[137],"computation.":[138],"We":[139],"conduct":[140],"extensive":[141],"experiments":[142],"three":[144],"real":[145],"datasets":[146],"verify":[148],"superiority":[150],"proposed":[153],"framework.":[154]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":4},{"year":2016,"cited_by_count":7},{"year":2015,"cited_by_count":5}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}