{"id":"https://openalex.org/W2803816741","doi":"https://doi.org/10.1145/3211954.3211959","title":"StreamScope: Automatic Pattern Discovery over Data Streams","display_name":"StreamScope: Automatic Pattern Discovery over Data Streams","publication_year":2018,"publication_date":"2018-05-22","ids":{"openalex":"https://openalex.org/W2803816741","doi":"https://doi.org/10.1145/3211954.3211959","mag":"2803816741"},"language":"en","primary_location":{"id":"doi:10.1145/3211954.3211959","doi":"https://doi.org/10.1145/3211954.3211959","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3211954.3211959","pdf_url":null,"source":{"id":"https://openalex.org/S7407113746","display_name":"International Workshop on Exploiting Artificial Intelligence Techniques for Data Management (aiDM)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the First International Workshop on Exploiting Artificial Intelligence Techniques for Data Management","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5072386702","display_name":"Kouki Kawabata","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I96036126","display_name":"Kumamoto University","ror":"https://ror.org/02cgss904","country_code":"JP","type":"education","lineage":["https://openalex.org/I96036126"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kouki Kawabata","raw_affiliation_strings":["Kumamoto University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kumamoto University","institution_ids":["https://openalex.org/I96036126"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005415598","display_name":"Yasuko Matsubara","orcid":"https://orcid.org/0000-0003-3566-7721","observed_orcids":["https://orcid.org/0000-0003-3566-7721"]},"institutions":[{"id":"https://openalex.org/I96036126","display_name":"Kumamoto University","ror":"https://ror.org/02cgss904","country_code":"JP","type":"education","lineage":["https://openalex.org/I96036126"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yasuko Matsubara","raw_affiliation_strings":["Kumamoto University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kumamoto University","institution_ids":["https://openalex.org/I96036126"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089668362","display_name":"Yasushi Sakurai","orcid":"https://orcid.org/0000-0001-7258-2642","observed_orcids":["https://orcid.org/0000-0001-7258-2642"]},"institutions":[{"id":"https://openalex.org/I96036126","display_name":"Kumamoto University","ror":"https://ror.org/02cgss904","country_code":"JP","type":"education","lineage":["https://openalex.org/I96036126"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yasushi Sakurai","raw_affiliation_strings":["Kumamoto University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kumamoto University","institution_ids":["https://openalex.org/I96036126"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I96036126"],"apc_list":null,"apc_paid":null,"fwci":0.2207,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.33281323,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":87,"max":93},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.45239999890327454,"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":0.45239999890327454,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.24950000643730164,"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/T10317","display_name":"Advanced Database Systems and Queries","score":0.1462000012397766,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/data-stream-mining","display_name":"data stream mining","score":0.7120000123977661},{"id":"https://openalex.org/keywords/event-streams","display_name":"event streams","score":0.5600000023841858},{"id":"https://openalex.org/keywords/pattern-discovery","display_name":"pattern discovery","score":0.652999997138977},{"id":"https://openalex.org/keywords/iot-data","display_name":"IoT data","score":0.5899999737739563}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8684201240539551},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.7896328568458557},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6829637289047241},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.5404627323150635},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.5294556021690369},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5013225078582764},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4746055006980896},{"id":"https://openalex.org/C42090638","wikidata":"https://www.wikidata.org/wiki/Q4048907","display_name":"STREAMS","level":2,"score":0.448589026927948},{"id":"https://openalex.org/C2778484313","wikidata":"https://www.wikidata.org/wiki/Q1172540","display_name":"Data stream","level":2,"score":0.44322314858436584},{"id":"https://openalex.org/C2777611316","wikidata":"https://www.wikidata.org/wiki/Q39045282","display_name":"Streaming data","level":2,"score":0.4171311855316162},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.32695019245147705},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.12686777114868164},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3211954.3211959","doi":"https://doi.org/10.1145/3211954.3211959","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3211954.3211959","pdf_url":null,"source":{"id":"https://openalex.org/S7407113746","display_name":"International Workshop on Exploiting Artificial Intelligence Techniques for Data Management (aiDM)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the First International Workshop on Exploiting Artificial Intelligence Techniques for Data Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G7749747368","display_name":"Realtime Data Mining for Online Activities","funder_award_id":"16K12430","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G7949078958","display_name":"Development of Methods for Social Information Analysis and Behavior Prediction Based on Web Information","funder_award_id":"18H03245","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W99176154","https://openalex.org/W1826290430","https://openalex.org/W1973222433","https://openalex.org/W1981398125","https://openalex.org/W1995264501","https://openalex.org/W1997741691","https://openalex.org/W1998901634","https://openalex.org/W2049344225","https://openalex.org/W2054685200","https://openalex.org/W2077760583","https://openalex.org/W2085799322","https://openalex.org/W2095897464","https://openalex.org/W2097098223","https://openalex.org/W2099302229","https://openalex.org/W2101460669","https://openalex.org/W2101618658","https://openalex.org/W2111619626","https://openalex.org/W2126626732","https://openalex.org/W2141806397","https://openalex.org/W2153982189","https://openalex.org/W2157940332","https://openalex.org/W2163150150","https://openalex.org/W2200183807","https://openalex.org/W2341645695","https://openalex.org/W2508807458","https://openalex.org/W2522231769","https://openalex.org/W2626473047","https://openalex.org/W2777788452","https://openalex.org/W4212863985","https://openalex.org/W4231029117","https://openalex.org/W4288598360","https://openalex.org/W6884764884"],"related_works":["https://openalex.org/W2987028103","https://openalex.org/W2948751990","https://openalex.org/W7095604552","https://openalex.org/W2010004246","https://openalex.org/W2576090100","https://openalex.org/W2054685200","https://openalex.org/W1981058017","https://openalex.org/W7097791397","https://openalex.org/W6884764884","https://openalex.org/W2112965067"],"abstract_inverted_index":{"Given":[0],"a":[1,47,51,59,103],"large":[2],"volume":[3],"of":[4,94,105,129,139,148,171],"multi-dimensional":[5],"data":[6,150],"streams,":[7],"such":[8,122],"as":[9],"that":[10,64,159],"produced":[11],"by":[12,110],"IoT":[13],"applications,":[14],"finance":[15],"and":[16,26,97,119,124,165,174],"online":[17],"web-click":[18],"logs,":[19],"how":[20,34],"can":[21,35,161],"we":[22,36,57],"discover":[23],"typical":[24],"patterns":[25,40,70,123,164],"compress":[27],"them":[28,130],"into":[29,102],"compact":[30],"models?":[31],"In":[32,54],"addition,":[33],"incrementally":[37,120],"distinguish":[38],"multiple":[39,106],"while":[41],"considering":[42],"the":[43,82,100,137,146,149],"information":[44],"obtained":[45],"from":[46,72],"pattern":[48],"found":[49],"in":[50,169],"streaming":[52,60],"setting?":[53],"this":[55],"paper,":[56],"propose":[58],"algorithm,":[61],"namely":[62],"StreamScope,":[63],"is":[65,87,115,135],"designed":[66],"to":[67],"find":[68,162],"intuitive":[69],"efficiently":[71],"event":[73],"streams":[74,96,101],"evolving":[75],"over":[76,177],"time.":[77],"Our":[78,152],"proposed":[79],"method":[80,141,181],"has":[81],"following":[83],"properties:":[84],"(a)":[85],"it":[86,89,114,117,134],"effective:":[88],"operates":[90],"on":[91,145,155],"semi-infinite":[92],"collections":[93],"co-evolving":[95],"summarizes":[98],"all":[99],"set":[104],"discrete":[107],"segments":[108],"grouped":[109],"their":[111],"similarities.":[112],"(b)":[113],"automatic:":[116],"automatically":[118],"recognizes":[121],"generates":[125],"models":[126],"for":[127],"each":[128],"if":[131],"necessary;":[132],"(c)":[133],"scalable:":[136],"complexity":[138],"our":[140],"does":[142],"not":[143],"depend":[144],"length":[147],"streams.":[151],"extensive":[153],"experiments":[154],"real":[156],"datasets":[157],"demonstrate":[158],"StreamScope":[160],"meaningful":[163],"achieve":[166],"great":[167],"improvements":[168],"terms":[170],"computational":[172],"time":[173],"memory":[175],"space":[176],"its":[178],"full":[179],"batch":[180],"competitors.":[182]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-11-12T12:28:57.059296","created_date":"2018-06-01T00:00:00"}