{"id":"https://openalex.org/W2902708880","doi":"https://doi.org/10.14778/3282495.3282498","title":"The lernaean hydra of data series similarity search","display_name":"The lernaean hydra of data series similarity search","publication_year":2018,"publication_date":"2018-10-01","ids":{"openalex":"https://openalex.org/W2902708880","doi":"https://doi.org/10.14778/3282495.3282498","mag":"2902708880"},"language":"en","primary_location":{"id":"doi:10.14778/3282495.3282498","is_oa":false,"landing_page_url":"https://doi.org/10.14778/3282495.3282498","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/A5049562331","display_name":"Karima Echihabi","orcid":"https://orcid.org/0000-0001-8095-6608"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Karima Echihabi","raw_affiliation_strings":["Mohammed V Univ"],"affiliations":[{"raw_affiliation_string":"Mohammed V Univ","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028953147","display_name":"Kostas Zoumpatianos","orcid":"https://orcid.org/0000-0002-6221-8254"},"institutions":[{"id":"https://openalex.org/I2801851002","display_name":"Harvard University Press","ror":"https://ror.org/006v7bf86","country_code":"US","type":"other","lineage":["https://openalex.org/I136199984","https://openalex.org/I2801851002"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kostas Zoumpatianos","raw_affiliation_strings":["Harvard Univ"],"affiliations":[{"raw_affiliation_string":"Harvard Univ","institution_ids":["https://openalex.org/I2801851002"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053726723","display_name":"Themis Palpanas","orcid":"https://orcid.org/0000-0002-8031-0265"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Themis Palpanas","raw_affiliation_strings":["Paris Descartes Univ"],"affiliations":[{"raw_affiliation_string":"Paris Descartes Univ","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065627637","display_name":"Houda Benbrahim","orcid":"https://orcid.org/0009-0005-2797-212X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Houda Benbrahim","raw_affiliation_strings":["Mohammed V Univ"],"affiliations":[{"raw_affiliation_string":"Mohammed V Univ","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5049562331"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":8.092,"has_fulltext":false,"cited_by_count":79,"citation_normalized_percentile":{"value":0.98282835,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"12","issue":"2","first_page":"112","last_page":"127"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9998000264167786,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9922000169754028,"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":0.9872999787330627,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/terminology","display_name":"Terminology","score":0.802911639213562},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6935992240905762},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.661325216293335},{"id":"https://openalex.org/keywords/strengths-and-weaknesses","display_name":"Strengths and weaknesses","score":0.612443208694458},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5958232879638672},{"id":"https://openalex.org/keywords/confusion","display_name":"Confusion","score":0.5295910239219666},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.5135526657104492},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5094526410102844},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5026872158050537},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.48217979073524475},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4608772099018097},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4295429587364197},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3176761269569397},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10616925358772278}],"concepts":[{"id":"https://openalex.org/C547195049","wikidata":"https://www.wikidata.org/wiki/Q1725664","display_name":"Terminology","level":2,"score":0.802911639213562},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6935992240905762},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.661325216293335},{"id":"https://openalex.org/C63882131","wikidata":"https://www.wikidata.org/wiki/Q17122954","display_name":"Strengths and weaknesses","level":2,"score":0.612443208694458},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5958232879638672},{"id":"https://openalex.org/C2781140086","wikidata":"https://www.wikidata.org/wiki/Q557945","display_name":"Confusion","level":2,"score":0.5295910239219666},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.5135526657104492},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5094526410102844},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5026872158050537},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.48217979073524475},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4608772099018097},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4295429587364197},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3176761269569397},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10616925358772278},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","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/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C11171543","wikidata":"https://www.wikidata.org/wiki/Q41630","display_name":"Psychoanalysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.14778/3282495.3282498","is_oa":false,"landing_page_url":"https://doi.org/10.14778/3282495.3282498","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"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":78,"referenced_works":["https://openalex.org/W53887678","https://openalex.org/W116902681","https://openalex.org/W145669980","https://openalex.org/W190850039","https://openalex.org/W642889137","https://openalex.org/W1495933060","https://openalex.org/W1499049447","https://openalex.org/W1502916507","https://openalex.org/W1514224985","https://openalex.org/W1541459201","https://openalex.org/W1552094045","https://openalex.org/W1555794464","https://openalex.org/W1610282999","https://openalex.org/W1853995153","https://openalex.org/W1970754582","https://openalex.org/W1971927246","https://openalex.org/W1973943669","https://openalex.org/W1984710256","https://openalex.org/W1989037929","https://openalex.org/W1990591351","https://openalex.org/W1996794795","https://openalex.org/W2008515415","https://openalex.org/W2016944175","https://openalex.org/W2025376161","https://openalex.org/W2028020839","https://openalex.org/W2029767187","https://openalex.org/W2042459866","https://openalex.org/W2053062040","https://openalex.org/W2062983764","https://openalex.org/W2066796814","https://openalex.org/W2069261761","https://openalex.org/W2077720176","https://openalex.org/W2077815765","https://openalex.org/W2083236658","https://openalex.org/W2091921805","https://openalex.org/W2095223629","https://openalex.org/W2097747115","https://openalex.org/W2098759488","https://openalex.org/W2099302229","https://openalex.org/W2106224901","https://openalex.org/W2107627518","https://openalex.org/W2109806013","https://openalex.org/W2110704543","https://openalex.org/W2115933183","https://openalex.org/W2117157603","https://openalex.org/W2118269922","https://openalex.org/W2119323564","https://openalex.org/W2122233046","https://openalex.org/W2122646361","https://openalex.org/W2123049307","https://openalex.org/W2128061541","https://openalex.org/W2138011093","https://openalex.org/W2151135734","https://openalex.org/W2161621125","https://openalex.org/W2162756694","https://openalex.org/W2266934531","https://openalex.org/W2292011317","https://openalex.org/W2296028074","https://openalex.org/W2318810549","https://openalex.org/W2405230789","https://openalex.org/W2427881153","https://openalex.org/W2468923260","https://openalex.org/W2513211580","https://openalex.org/W2529438039","https://openalex.org/W2555077524","https://openalex.org/W2623413278","https://openalex.org/W2702877955","https://openalex.org/W2744237760","https://openalex.org/W2766751560","https://openalex.org/W2794911547","https://openalex.org/W2883014178","https://openalex.org/W2896497283","https://openalex.org/W2902708880","https://openalex.org/W2914343162","https://openalex.org/W2999763220","https://openalex.org/W3008323075","https://openalex.org/W3165728814","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2350593162","https://openalex.org/W2390350206","https://openalex.org/W1969477129","https://openalex.org/W2921208823","https://openalex.org/W2131808775","https://openalex.org/W2353483812","https://openalex.org/W2360756181","https://openalex.org/W2374093222","https://openalex.org/W3154008094","https://openalex.org/W2359533638"],"abstract_inverted_index":{"Increasingly":[0],"large":[1],"data":[2,21,116],"series":[3,22,117],"collections":[4,23],"are":[5],"becoming":[6],"commonplace":[7],"across":[8],"many":[9],"different":[10,93],"domains":[11],"and":[12,33,83,105,130,135],"applications.":[13],"A":[14],"key":[15],"operation":[16],"in":[17,48,102,165],"the":[18,36,49,53,61,73,92,103,107,113,123,128,139,151,159,166],"analysis":[19],"of":[20,31,52,66,76,95,112,115,132,153],"is":[24,69],"similarity":[25,96,118],"search,":[26],"which":[27,78],"has":[28,79],"attracted":[29],"lots":[30],"attention":[32],"effort":[34],"over":[35],"past":[37],"two":[38],"decades.":[39],"Even":[40],"though":[41],"several":[42],"relevant":[43],"approaches":[44],"have":[45,99],"been":[46,100],"proposed":[47],"literature,":[50],"none":[51],"existing":[54],"studies":[55],"provides":[56],"a":[57],"detailed":[58],"evaluation":[59,111],"against":[60],"available":[62],"alternatives.":[63],"The":[64],"lack":[65],"comparative":[67],"results":[68],"further":[70,163],"exacerbated":[71],"by":[72,149],"non-standard":[74],"use":[75,143,146],"terminology,":[77],"led":[80],"to":[81,142],"confusion":[82],"misconceptions.":[84],"In":[85],"this":[86],"paper,":[87],"we":[88,126],"provide":[89],"definitions":[90],"for":[91,138,161],"flavors":[94],"search":[97,119],"that":[98],"studied":[101],"past,":[104],"present":[106],"first":[108],"systematic":[109],"experimental":[110,124],"efficiency":[114],"techniques.":[120],"Based":[121],"on":[122],"results,":[125],"describe":[127],"strengths":[129],"weaknesses":[131],"each":[133,154],"approach":[134,141],"give":[136],"recommendations":[137],"best":[140],"under":[144],"typical":[145],"cases.":[147],"Finally,":[148],"identifying":[150],"shortcomings":[152],"method,":[155],"our":[156],"findings":[157],"lay":[158],"ground":[160],"solid":[162],"developments":[164],"field.":[167]},"counts_by_year":[{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":12},{"year":2020,"cited_by_count":26},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
